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Publisher: Springer-Verlag (Total: 2351 journals)

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Showing 1 - 200 of 2351 Journals sorted alphabetically
3D Printing in Medicine     Open Access  
3D Research     Hybrid Journal   (Followers: 21, SJR: 0.222, CiteScore: 1)
4OR: A Quarterly J. of Operations Research     Hybrid Journal   (Followers: 10, SJR: 0.825, CiteScore: 1)
AAPS J.     Hybrid Journal   (Followers: 22, SJR: 1.118, CiteScore: 4)
AAPS PharmSciTech     Hybrid Journal   (Followers: 7, SJR: 0.752, CiteScore: 3)
Abdominal Imaging     Hybrid Journal   (Followers: 14, SJR: 0.866, CiteScore: 2)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 4, SJR: 0.439, CiteScore: 0)
Academic Psychiatry     Full-text available via subscription   (Followers: 23, SJR: 0.53, CiteScore: 1)
Academic Questions     Hybrid Journal   (Followers: 8, SJR: 0.106, CiteScore: 0)
Accreditation and Quality Assurance: J. for Quality, Comparability and Reliability in Chemical Measurement     Hybrid Journal   (Followers: 26, SJR: 0.316, CiteScore: 1)
Acoustical Physics     Hybrid Journal   (Followers: 11, SJR: 0.359, CiteScore: 1)
Acoustics Australia     Hybrid Journal   (SJR: 0.232, CiteScore: 1)
Acta Analytica     Hybrid Journal   (Followers: 7, SJR: 0.367, CiteScore: 0)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 1, SJR: 0.675, CiteScore: 1)
Acta Biotheoretica     Hybrid Journal   (Followers: 4, SJR: 0.284, CiteScore: 1)
Acta Diabetologica     Hybrid Journal   (Followers: 18, SJR: 1.587, CiteScore: 3)
Acta Endoscopica     Hybrid Journal   (Followers: 1)
acta ethologica     Hybrid Journal   (Followers: 4, SJR: 0.769, CiteScore: 1)
Acta Geochimica     Hybrid Journal   (Followers: 6, SJR: 0.24, CiteScore: 1)
Acta Geodaetica et Geophysica     Hybrid Journal   (Followers: 2, SJR: 0.305, CiteScore: 1)
Acta Geotechnica     Hybrid Journal   (Followers: 7, SJR: 1.588, CiteScore: 3)
Acta Informatica     Hybrid Journal   (Followers: 5, SJR: 0.517, CiteScore: 1)
Acta Mathematica     Hybrid Journal   (Followers: 12, SJR: 7.066, CiteScore: 3)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2, SJR: 0.452, CiteScore: 1)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 6, SJR: 0.379, CiteScore: 1)
Acta Mathematica Vietnamica     Hybrid Journal   (SJR: 0.27, CiteScore: 0)
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal   (SJR: 0.208, CiteScore: 0)
Acta Mechanica     Hybrid Journal   (Followers: 21, SJR: 1.04, CiteScore: 2)
Acta Mechanica Sinica     Hybrid Journal   (Followers: 5, SJR: 0.607, CiteScore: 2)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 7, SJR: 0.576, CiteScore: 2)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3, SJR: 0.638, CiteScore: 1)
Acta Neurochirurgica     Hybrid Journal   (Followers: 6, SJR: 0.822, CiteScore: 2)
Acta Neurologica Belgica     Hybrid Journal   (Followers: 1, SJR: 0.376, CiteScore: 1)
Acta Neuropathologica     Hybrid Journal   (Followers: 5, SJR: 7.589, CiteScore: 12)
Acta Oceanologica Sinica     Hybrid Journal   (Followers: 3, SJR: 0.334, CiteScore: 1)
Acta Parasitologica     Hybrid Journal   (Followers: 10, SJR: 0.641, CiteScore: 1)
Acta Physiologiae Plantarum     Hybrid Journal   (Followers: 2, SJR: 0.574, CiteScore: 2)
Acta Politica     Hybrid Journal   (Followers: 14, SJR: 0.605, CiteScore: 1)
Activitas Nervosa Superior     Hybrid Journal   (SJR: 0.147, CiteScore: 0)
adhäsion KLEBEN & DICHTEN     Hybrid Journal   (Followers: 7, SJR: 0.103, CiteScore: 0)
ADHD Attention Deficit and Hyperactivity Disorders     Hybrid Journal   (Followers: 23, SJR: 0.72, CiteScore: 2)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 9)
Administration and Policy in Mental Health and Mental Health Services Research     Partially Free   (Followers: 16, SJR: 1.005, CiteScore: 2)
Adsorption     Hybrid Journal   (Followers: 4, SJR: 0.703, CiteScore: 2)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 4, SJR: 0.698, CiteScore: 1)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 37, SJR: 0.956, CiteScore: 2)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19, SJR: 0.812, CiteScore: 1)
Advances in Contraception     Hybrid Journal   (Followers: 3)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 51, SJR: 1.09, CiteScore: 1)
Advances in Gerontology     Partially Free   (Followers: 8, SJR: 0.144, CiteScore: 0)
Advances in Health Sciences Education     Hybrid Journal   (Followers: 29, SJR: 1.64, CiteScore: 2)
Advances in Manufacturing     Hybrid Journal   (Followers: 3, SJR: 0.475, CiteScore: 2)
Advances in Polymer Science     Hybrid Journal   (Followers: 43, SJR: 1.04, CiteScore: 3)
Advances in Therapy     Hybrid Journal   (Followers: 5, SJR: 1.075, CiteScore: 3)
Aegean Review of the Law of the Sea and Maritime Law     Hybrid Journal   (Followers: 6)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2, SJR: 0.517, CiteScore: 1)
Aerobiologia     Hybrid Journal   (Followers: 3, SJR: 0.673, CiteScore: 2)
Aesthetic Plastic Surgery     Hybrid Journal   (Followers: 9, SJR: 0.825, CiteScore: 1)
African Archaeological Review     Hybrid Journal   (Followers: 16, SJR: 0.862, CiteScore: 1)
Afrika Matematika     Hybrid Journal   (Followers: 1, SJR: 0.235, CiteScore: 0)
AGE     Hybrid Journal   (Followers: 7)
Ageing Intl.     Hybrid Journal   (Followers: 7, SJR: 0.39, CiteScore: 1)
Aggiornamenti CIO     Hybrid Journal   (Followers: 1)
Aging Clinical and Experimental Research     Hybrid Journal   (Followers: 3, SJR: 0.67, CiteScore: 2)
Agricultural Research     Hybrid Journal   (Followers: 5, SJR: 0.276, CiteScore: 1)
Agriculture and Human Values     Hybrid Journal   (Followers: 14, SJR: 1.173, CiteScore: 3)
Agroforestry Systems     Hybrid Journal   (Followers: 19, SJR: 0.663, CiteScore: 1)
Agronomy for Sustainable Development     Hybrid Journal   (Followers: 12, SJR: 1.864, CiteScore: 6)
AI & Society     Hybrid Journal   (Followers: 8, SJR: 0.227, CiteScore: 1)
AIDS and Behavior     Hybrid Journal   (Followers: 14, SJR: 1.792, CiteScore: 3)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 4, SJR: 0.862, CiteScore: 3)
Akupunktur & Aurikulomedizin     Full-text available via subscription   (Followers: 1)
Algebra and Logic     Hybrid Journal   (Followers: 6, SJR: 0.531, CiteScore: 0)
Algebra Universalis     Hybrid Journal   (Followers: 2, SJR: 0.583, CiteScore: 1)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1, SJR: 1.095, CiteScore: 1)
Algorithmica     Hybrid Journal   (Followers: 9, SJR: 0.56, CiteScore: 1)
Allergo J.     Full-text available via subscription   (Followers: 1, SJR: 0.234, CiteScore: 0)
Allergo J. Intl.     Hybrid Journal   (Followers: 2)
Alpine Botany     Hybrid Journal   (Followers: 5, SJR: 1.11, CiteScore: 3)
ALTEX : Alternatives to Animal Experimentation     Open Access   (Followers: 3)
AMBIO     Hybrid Journal   (Followers: 10, SJR: 1.569, CiteScore: 4)
American J. of Cardiovascular Drugs     Hybrid Journal   (Followers: 16, SJR: 0.951, CiteScore: 3)
American J. of Community Psychology     Hybrid Journal   (Followers: 28, SJR: 1.329, CiteScore: 2)
American J. of Criminal Justice     Hybrid Journal   (Followers: 8, SJR: 0.772, CiteScore: 1)
American J. of Cultural Sociology     Hybrid Journal   (Followers: 16, SJR: 0.46, CiteScore: 1)
American J. of Dance Therapy     Hybrid Journal   (Followers: 4, SJR: 0.181, CiteScore: 0)
American J. of Potato Research     Hybrid Journal   (Followers: 2, SJR: 0.611, CiteScore: 1)
American J. of Psychoanalysis     Hybrid Journal   (Followers: 21, SJR: 0.314, CiteScore: 0)
American Sociologist     Hybrid Journal   (Followers: 12, SJR: 0.35, CiteScore: 0)
Amino Acids     Hybrid Journal   (Followers: 8, SJR: 1.135, CiteScore: 3)
AMS Review     Partially Free   (Followers: 4)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7, SJR: 0.211, CiteScore: 1)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 5, SJR: 0.536, CiteScore: 1)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Analysis of Verbal Behavior     Hybrid Journal   (Followers: 5)
Analytical and Bioanalytical Chemistry     Hybrid Journal   (Followers: 32, SJR: 0.978, CiteScore: 3)
Anatomical Science Intl.     Hybrid Journal   (Followers: 2, SJR: 0.367, CiteScore: 1)
Angewandte Schmerztherapie und Palliativmedizin     Hybrid Journal  
Angiogenesis     Hybrid Journal   (Followers: 3, SJR: 2.177, CiteScore: 5)
Animal Cognition     Hybrid Journal   (Followers: 19, SJR: 1.389, CiteScore: 3)
Annales françaises de médecine d'urgence     Hybrid Journal   (Followers: 1, SJR: 0.192, CiteScore: 0)
Annales Henri Poincaré     Hybrid Journal   (Followers: 3, SJR: 1.097, CiteScore: 2)
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4, SJR: 0.438, CiteScore: 0)
Annali dell'Universita di Ferrara     Hybrid Journal   (SJR: 0.429, CiteScore: 0)
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1, SJR: 1.197, CiteScore: 1)
Annals of Biomedical Engineering     Hybrid Journal   (Followers: 18, SJR: 1.042, CiteScore: 3)
Annals of Combinatorics     Hybrid Journal   (Followers: 4, SJR: 0.932, CiteScore: 1)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Dyslexia     Hybrid Journal   (Followers: 10, SJR: 0.85, CiteScore: 2)
Annals of Finance     Hybrid Journal   (Followers: 30, SJR: 0.579, CiteScore: 1)
Annals of Forest Science     Hybrid Journal   (Followers: 7, SJR: 0.986, CiteScore: 2)
Annals of Global Analysis and Geometry     Hybrid Journal   (Followers: 1, SJR: 1.228, CiteScore: 1)
Annals of Hematology     Hybrid Journal   (Followers: 15, SJR: 1.043, CiteScore: 2)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12, SJR: 0.413, CiteScore: 1)
Annals of Microbiology     Hybrid Journal   (Followers: 10, SJR: 0.479, CiteScore: 2)
Annals of Nuclear Medicine     Hybrid Journal   (Followers: 4, SJR: 0.687, CiteScore: 2)
Annals of Operations Research     Hybrid Journal   (Followers: 10, SJR: 0.943, CiteScore: 2)
Annals of Ophthalmology     Hybrid Journal   (Followers: 11)
Annals of Regional Science     Hybrid Journal   (Followers: 7, SJR: 0.614, CiteScore: 1)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annals of Solid and Structural Mechanics     Hybrid Journal   (Followers: 9, SJR: 0.239, CiteScore: 1)
Annals of Surgical Oncology     Hybrid Journal   (Followers: 13, SJR: 1.986, CiteScore: 4)
Annals of Telecommunications     Hybrid Journal   (Followers: 9, SJR: 0.223, CiteScore: 1)
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1, SJR: 1.495, CiteScore: 1)
Antonie van Leeuwenhoek     Hybrid Journal   (Followers: 5, SJR: 0.834, CiteScore: 2)
Apidologie     Hybrid Journal   (Followers: 4, SJR: 1.22, CiteScore: 3)
APOPTOSIS     Hybrid Journal   (Followers: 8, SJR: 1.424, CiteScore: 4)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2, SJR: 0.294, CiteScore: 1)
Applications of Mathematics     Hybrid Journal   (Followers: 2, SJR: 0.602, CiteScore: 1)
Applied Biochemistry and Biotechnology     Hybrid Journal   (Followers: 43, SJR: 0.571, CiteScore: 2)
Applied Biochemistry and Microbiology     Hybrid Journal   (Followers: 17, SJR: 0.21, CiteScore: 1)
Applied Cancer Research     Open Access  
Applied Categorical Structures     Hybrid Journal   (Followers: 2, SJR: 0.49, CiteScore: 0)
Applied Composite Materials     Hybrid Journal   (Followers: 49, SJR: 0.58, CiteScore: 2)
Applied Entomology and Zoology     Partially Free   (Followers: 3, SJR: 0.422, CiteScore: 1)
Applied Geomatics     Hybrid Journal   (Followers: 3, SJR: 0.733, CiteScore: 3)
Applied Geophysics     Hybrid Journal   (Followers: 8, SJR: 0.488, CiteScore: 1)
Applied Intelligence     Hybrid Journal   (Followers: 12, SJR: 0.6, CiteScore: 2)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4, SJR: 0.319, CiteScore: 1)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 6, SJR: 0.886, CiteScore: 1)
Applied Mathematics - A J. of Chinese Universities     Hybrid Journal   (SJR: 0.17, CiteScore: 0)
Applied Mathematics and Mechanics     Hybrid Journal   (Followers: 5, SJR: 0.461, CiteScore: 1)
Applied Microbiology and Biotechnology     Hybrid Journal   (Followers: 63, SJR: 1.182, CiteScore: 4)
Applied Physics A     Hybrid Journal   (Followers: 9, SJR: 0.481, CiteScore: 2)
Applied Physics B: Lasers and Optics     Hybrid Journal   (Followers: 24, SJR: 0.74, CiteScore: 2)
Applied Psychophysiology and Biofeedback     Hybrid Journal   (Followers: 8, SJR: 0.519, CiteScore: 2)
Applied Research in Quality of Life     Hybrid Journal   (Followers: 12, SJR: 0.316, CiteScore: 1)
Applied Solar Energy     Hybrid Journal   (Followers: 18, SJR: 0.225, CiteScore: 0)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4, SJR: 0.542, CiteScore: 1)
Aquaculture Intl.     Hybrid Journal   (Followers: 23, SJR: 0.591, CiteScore: 2)
Aquarium Sciences and Conservation     Hybrid Journal   (Followers: 1)
Aquatic Ecology     Hybrid Journal   (Followers: 33, SJR: 0.656, CiteScore: 2)
Aquatic Geochemistry     Hybrid Journal   (Followers: 4, SJR: 0.591, CiteScore: 1)
Aquatic Sciences     Hybrid Journal   (Followers: 13, SJR: 1.109, CiteScore: 3)
Arabian J. for Science and Engineering     Hybrid Journal   (Followers: 5, SJR: 0.303, CiteScore: 1)
Arabian J. of Geosciences     Hybrid Journal   (Followers: 2, SJR: 0.319, CiteScore: 1)
Archaeological and Anthropological Sciences     Hybrid Journal   (Followers: 20, SJR: 1.052, CiteScore: 2)
Archaeologies     Hybrid Journal   (Followers: 12, SJR: 0.224, CiteScore: 0)
Archiv der Mathematik     Hybrid Journal   (Followers: 1, SJR: 0.725, CiteScore: 1)
Archival Science     Hybrid Journal   (Followers: 60, SJR: 0.745, CiteScore: 2)
Archive for History of Exact Sciences     Hybrid Journal   (Followers: 8, SJR: 0.186, CiteScore: 1)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 2, SJR: 0.909, CiteScore: 1)
Archive for Rational Mechanics and Analysis     Hybrid Journal   (SJR: 3.93, CiteScore: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5, SJR: 0.79, CiteScore: 2)
Archives and Museum Informatics     Hybrid Journal   (Followers: 144, SJR: 0.101, CiteScore: 0)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5, SJR: 1.41, CiteScore: 5)
Archives of Dermatological Research     Hybrid Journal   (Followers: 7, SJR: 1.006, CiteScore: 2)
Archives of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 14, SJR: 0.773, CiteScore: 2)
Archives of Gynecology and Obstetrics     Hybrid Journal   (Followers: 16, SJR: 0.956, CiteScore: 2)
Archives of Microbiology     Hybrid Journal   (Followers: 8, SJR: 0.644, CiteScore: 2)
Archives of Orthopaedic and Trauma Surgery     Hybrid Journal   (Followers: 8, SJR: 1.146, CiteScore: 2)
Archives of Osteoporosis     Hybrid Journal   (Followers: 2, SJR: 0.71, CiteScore: 2)
Archives of Sexual Behavior     Hybrid Journal   (Followers: 10, SJR: 1.493, CiteScore: 3)
Archives of Toxicology     Hybrid Journal   (Followers: 17, SJR: 1.541, CiteScore: 5)
Archives of Virology     Hybrid Journal   (Followers: 5, SJR: 0.973, CiteScore: 2)
Archives of Women's Mental Health     Hybrid Journal   (Followers: 14, SJR: 1.274, CiteScore: 3)
Archivio di Ortopedia e Reumatologia     Hybrid Journal  
Archivum Immunologiae et Therapiae Experimentalis     Hybrid Journal   (Followers: 2, SJR: 0.946, CiteScore: 3)
ArgoSpine News & J.     Hybrid Journal  
Argumentation     Hybrid Journal   (Followers: 5, SJR: 0.349, CiteScore: 1)
Arid Ecosystems     Hybrid Journal   (Followers: 2, SJR: 0.2, CiteScore: 0)
Arkiv för Matematik     Hybrid Journal   (Followers: 1, SJR: 0.766, CiteScore: 1)
Arnold Mathematical J.     Hybrid Journal   (Followers: 1, SJR: 0.355, CiteScore: 0)
Arthropod-Plant Interactions     Hybrid Journal   (Followers: 2, SJR: 0.839, CiteScore: 2)
Arthroskopie     Hybrid Journal   (Followers: 1, SJR: 0.131, CiteScore: 0)
Artificial Intelligence and Law     Hybrid Journal   (Followers: 11, SJR: 0.937, CiteScore: 2)
Artificial Intelligence Review     Hybrid Journal   (Followers: 14, SJR: 0.833, CiteScore: 4)
Artificial Life and Robotics     Hybrid Journal   (Followers: 9, SJR: 0.226, CiteScore: 0)
Asia Europe J.     Hybrid Journal   (Followers: 5, SJR: 0.504, CiteScore: 1)
Asia Pacific Education Review     Hybrid Journal   (Followers: 12, SJR: 0.479, CiteScore: 1)
Asia Pacific J. of Management     Hybrid Journal   (Followers: 16, SJR: 1.185, CiteScore: 2)
Asia-Pacific Education Researcher     Hybrid Journal   (Followers: 12, SJR: 0.353, CiteScore: 1)
Asia-Pacific Financial Markets     Hybrid Journal   (Followers: 2, SJR: 0.187, CiteScore: 0)
Asia-Pacific J. of Atmospheric Sciences     Hybrid Journal   (Followers: 19, SJR: 0.855, CiteScore: 1)
Asian Business & Management     Hybrid Journal   (Followers: 9, SJR: 0.378, CiteScore: 1)
Asian J. of Business Ethics     Hybrid Journal   (Followers: 9)
Asian J. of Criminology     Hybrid Journal   (Followers: 5, SJR: 0.543, CiteScore: 1)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 3, SJR: 0.548, CiteScore: 1)
AStA Wirtschafts- und Sozialstatistisches Archiv     Hybrid Journal   (Followers: 5, SJR: 0.183, CiteScore: 0)
ästhetische dermatologie & kosmetologie     Full-text available via subscription  

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Journal Cover
Artificial Intelligence Review
Journal Prestige (SJR): 0.833
Citation Impact (citeScore): 4
Number of Followers: 14  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-7462 - ISSN (Online) 0269-2821
Published by Springer-Verlag Homepage  [2351 journals]
  • A survey of virtual sample generation technology for face recognition
    • Authors: Lingjun Li; Yali Peng; Guoyong Qiu; Zengguo Sun; Shigang Liu
      Pages: 1 - 20
      Abstract: Despite considerable advances made in face recognition in recent years, the recognition performance still suffers from insufficient training samples. Hence, various algorithms have been proposed for addressing the problems of small sample size with dramatic variations in illuminations, poses and facial expressions in face recognition. Among these algorithms, the virtual sample generation technology achieves promising performance with reasonable and effective mathematical function and easy implementation. In this paper, we systematically summarize the research progress in the virtual sample generation technology for face recognition and categorize the existing methods into three groups, namely, (1) construction of virtual face images based on the face structure; (2) construction of virtual face images based on the idea of perturbation and distribution function of samples; (3) construction of virtual face images based on the sample viewpoint. We carry out thorough and comprehensive comparative study in which different methods are compared by conducting an in-depth analysis on them. It demonstrates the significant advantage of combining the virtual sample generation technology with representation based methods.
      PubDate: 2018-06-01
      DOI: 10.1007/s10462-016-9537-z
      Issue No: Vol. 50, No. 1 (2018)
       
  • Knowledge-based recommendation: a review of ontology-based recommender
           systems for e-learning
    • Authors: John K. Tarus; Zhendong Niu; Ghulam Mustafa
      Pages: 21 - 48
      Abstract: Recommender systems in e-learning domain play an important role in assisting the learners to find useful and relevant learning materials that meet their learning needs. Personalized intelligent agents and recommender systems have been widely accepted as solutions towards overcoming information retrieval challenges by learners arising from information overload. Use of ontology for knowledge representation in knowledge-based recommender systems for e-learning has become an interesting research area. In knowledge-based recommendation for e-learning resources, ontology is used to represent knowledge about the learner and learning resources. Although a number of review studies have been carried out in the area of recommender systems, there are still gaps and deficiencies in the comprehensive literature review and survey in the specific area of ontology-based recommendation for e-learning. In this paper, we present a review of literature on ontology-based recommenders for e-learning. First, we analyze and classify the journal papers that were published from 2005 to 2014 in the field of ontology-based recommendation for e-learning. Secondly, we categorize the different recommendation techniques used by ontology-based e-learning recommenders. Thirdly, we categorize the knowledge representation technique, ontology type and ontology representation language used by ontology-based recommender systems, as well as types of learning resources recommended by e-learning recommenders. Lastly, we discuss the future trends of this recommendation approach in the context of e-learning. This study shows that use of ontology for knowledge representation in e-learning recommender systems can improve the quality of recommendations. It was also evident that hybridization of knowledge-based recommendation with other recommendation techniques can enhance the effectiveness of e-learning recommenders.
      PubDate: 2018-06-01
      DOI: 10.1007/s10462-017-9539-5
      Issue No: Vol. 50, No. 1 (2018)
       
  • Natural language based financial forecasting: a survey
    • Authors: Frank Z. Xing; Erik Cambria; Roy E. Welsch
      Pages: 49 - 73
      Abstract: Natural language processing (NLP), or the pragmatic research perspective of computational linguistics, has become increasingly powerful due to data availability and various techniques developed in the past decade. This increasing capability makes it possible to capture sentiments more accurately and semantics in a more nuanced way. Naturally, many applications are starting to seek improvements by adopting cutting-edge NLP techniques. Financial forecasting is no exception. As a result, articles that leverage NLP techniques to predict financial markets are fast accumulating, gradually establishing the research field of natural language based financial forecasting (NLFF), or from the application perspective, stock market prediction. This review article clarifies the scope of NLFF research by ordering and structuring techniques and applications from related work. The survey also aims to increase the understanding of progress and hotspots in NLFF, and bring about discussions across many different disciplines.
      PubDate: 2018-06-01
      DOI: 10.1007/s10462-017-9588-9
      Issue No: Vol. 50, No. 1 (2018)
       
  • Iterative ADP learning algorithms for discrete-time multi-player games
    • Authors: He Jiang; Huaguang Zhang
      Pages: 75 - 91
      Abstract: Adaptive dynamic programming (ADP) is an important branch of reinforcement learning to solve various optimal control issues. Most practical nonlinear systems are controlled by more than one controller. Each controller is a player, and to make a tradeoff between cooperation and conflict of these players can be viewed as a game. Multi-player games are divided into two main categories: zero-sum game and non-zero-sum game. To obtain the optimal control policy for each player, one needs to solve Hamilton–Jacobi–Isaacs equations for zero-sum games and a set of coupled Hamilton–Jacobi equations for non-zero-sum games. Unfortunately, these equations are generally difficult or even impossible to be solved analytically. To overcome this bottleneck, two ADP methods, including a modified gradient-descent-based online algorithm and a novel iterative offline learning approach, are proposed in this paper. Furthermore, to implement the proposed methods, we employ single-network structure, which obviously reduces computation burden compared with traditional multiple-network architecture. Simulation results demonstrate the effectiveness of our schemes.
      PubDate: 2018-06-01
      DOI: 10.1007/s10462-017-9603-1
      Issue No: Vol. 50, No. 1 (2018)
       
  • A Vietnamese adjective emotion dictionary based on exploitation of
           Vietnamese language characteristics
    • Authors: Vo Ngoc Phu; Vo Thi Ngoc Chau; Vo Thi Ngoc Tran; Nguyen Duy Dat
      Pages: 93 - 159
      Abstract: Emotion classification is used in many commercial applications and research applications. The semantic classification models (or sentiment classification methods) are based on the vocabulary of the emotion dictionary being studied and being used very much to this day. In this study, a Vietnamese sentiment dictionary includes Vietnamese terms (Vietnamese nouns, Vietnamese verbs, Vietnamese adjectives, etc.) which the valences (and polarities) are calculated by using Ochiai measure through Google search engine and many Vietnamese adjective phrases which the valences (and polarities) are identified based on Vietnamese language characteristics. The Vietnamese adjectives often bear emotion which values (or semantic scores) are not fixed and are changed when they appear in different contexts of these phrases. Therefore, if the Vietnamese adjectives bring sentiment and their semantic values (or their sentiment scores) are not changed in any context, then the results of the emotion classification are not high accuracy. We propose many rules based on Vietnamese language characteristics to determine the emotional values of the Vietnamese adjective phrases bearing sentiment in specific contexts. Our Vietnamese sentiment adjective dictionary is widely used in applications and researches of the Vietnamese semantic classification.
      PubDate: 2018-06-01
      DOI: 10.1007/s10462-017-9538-6
      Issue No: Vol. 50, No. 1 (2018)
       
  • Classification of asymptomatic and osteoarthritic knee gait patterns using
           gait analysis via deterministic learning
    • Authors: Wei Zeng; Limin Ma; Chengzhi Yuan; Fenglin Liu; Qinghui Wang; Ying Wang; Yu Zhang
      Abstract: Gait measures have received increasing attention in the evaluation of patients with knee osteoarthritis (OA). Comprehending gait parameters is an essential requirement for studying the causes of knee disorders. The aim of this work is to develop a new method to distinguish between asymptomatic (AS) and osteoarthritic knee gait patterns using gait analysis via deterministic learning. Spatiotemporal parameters and three-dimensional knee joint rotations and translations are measured and compared in 19 patients with knee OA and 28 AS control subjects during level walking. The classification approach consists of two stages: a training stage and a classification stage. In the training stage, gait features representing gait dynamics, including knee rotations and translations, are derived from the kinematic data of the knees in six-degree-of-freedom. Gait dynamics underlying gait patterns of AS control subjects and patients with knee OA are locally accurately approximated by radial basis function (RBF) neural networks. The obtained knowledge of approximated gait dynamics is stored in constant RBF networks. Gait patterns of AS control subjects and patients with knee OA constitute a training set. In the classification stage, a bank of dynamical estimators is constructed for all the training gait patterns. Prior knowledge of gait dynamics represented by the constant RBF networks is embedded in the estimators. By comparing the set of estimators with a test knee OA gait pattern to be classified, a set of classification errors are generated. The average \(L_1\) norms of the errors are taken as the classification measure between the dynamics of the training gait patterns and the dynamics of the test knee OA gait pattern according to the smallest error principle. Finally, experiments are carried out to demonstrate that the proposed method can effectively separate the gait patterns between the groups of AS control subjects and patients with knee OA. By using the two-fold cross-validation and leave-one-out cross-validation styles, the correct classification rates for knee OA gait patterns are reported to be 95.7 and 97.9%, respectively.
      PubDate: 2018-07-10
      DOI: 10.1007/s10462-018-9645-z
       
  • Recent granular computing frameworks for mining relational data
    • Authors: Piotr Hońko
      Abstract: A lot of data currently being collected is stored in databases with a relational structure. The process of knowledge discovery from such data is a more challenging task compared with single table data. Granular computing, which has successfully been applied to mining data storable in single tables, is a promising direction for discovering knowledge from relational data. This paper summarizes some recent developments in the area of application of granular computing to mining relational data. Four granular computing frameworks for processing relational data are introduced and compared. The paper shows how each of the frameworks represents relational data, constructs information granules and build patterns based on the granules. A generic system that can employ any of the frameworks to discover knowledge from relational data is also outlined.
      PubDate: 2018-06-30
      DOI: 10.1007/s10462-018-9643-1
       
  • Improving search engine optimization (SEO) by using hybrid modified MCDM
           models
    • Authors: Hung-Jia Tsuei; Wei-Ho Tsai; Fu-Te Pan; Gwo-Hshiung Tzeng
      Abstract: Search engine optimization (SEO) has been considered one of the most important techniques in internet marketing. This study establishes a decision model of search engine ranking for administrators to improve the performances of websites that satisfy users’ needs. To probe into the interrelationship and influential weights among criteria of SEO and evaluate the gaps of performance to achieve the aspiration level in real world, this research utilizes hybrid modified multiple criteria decision-making models, including decision-making trial and evaluation laboratory (DEMATEL), DEMATEL-based analytic network process (called DANP), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The empirical findings discover that the criteria of SEO possessed a self-effect relationship based on DEMATEL technique. According to the influential network relation map (INRM), external website optimization is the top priority dimension that needs to be improved when implementing SEO. Among the six criteria for evaluation, meta tags is the most significant criterion influencing search engine ranking, followed by keywords and website design. The evaluation of search engine ranking reveals that the website with lowest gap would be the optimal example for administrators of websites to make high ranking website during the time that this study is executed.
      PubDate: 2018-06-28
      DOI: 10.1007/s10462-018-9644-0
       
  • Recent progress in semantic image segmentation
    • Authors: Xiaolong Liu; Zhidong Deng; Yuhan Yang
      Abstract: Semantic image segmentation, which becomes one of the key applications in image processing and computer vision domain, has been used in multiple domains such as medical area and intelligent transportation. Lots of benchmark datasets are released for researchers to verify their algorithms. Semantic segmentation has been studied for many years. Since the emergence of Deep Neural Network (DNN), segmentation has made a tremendous progress. In this paper, we divide semantic image segmentation methods into two categories: traditional and recent DNN method. Firstly, we briefly summarize the traditional method as well as datasets released for segmentation, then we comprehensively investigate recent methods based on DNN which are described in the eight aspects: fully convolutional network, up-sample ways, FCN joint with CRF methods, dilated convolution approaches, progresses in backbone network, pyramid methods, Multi-level feature and multi-stage method, supervised, weakly-supervised and unsupervised methods. Finally, a conclusion in this area is drawn.
      PubDate: 2018-06-27
      DOI: 10.1007/s10462-018-9641-3
       
  • The investigation of neural networks performance in side-channel attacks
    • Authors: Yinan Kong; Ehsan Saeedi
      Abstract: Scientists have devoted a lot of affords to guarantee the safety of cryptosystems by improving cryptography algorithms, while these systems can still be vulnerable to side-channel information analysis based on neural networks (NNs) and principal component analysis (PCA). PCA can be used as a preprocessing stage, while NNs can learn the signature (power consumption and electromagnetic emission) of an instruction of a cryptography algorithm, and then recognizes it later automatically. This paper investigate the performance of NNs as a powerful classifier to analysis the side-channel information. For this purpose, an experimental investigation was conducted based on the power consumption and electromagnetic emission analysis of a field-programmable gate array implementation of elliptic curve cryptography. In our experimental results, the performance of different NNs topologies are compared which provide useful information for cryptosystem designers. In addition an efficient NN topology is introduced for characterization of side-channel information.
      PubDate: 2018-06-27
      DOI: 10.1007/s10462-018-9640-4
       
  • A survey of dynamic spectrum allocation based on reinforcement learning
           algorithms in cognitive radio networks
    • Authors: Yonghua Wang; Zifeng Ye; Pin Wan; Jiajun Zhao
      Abstract: Cognitive radio is an emerging technology that is considered to be an evolution for software device radio in which cognition and decision-making components are included. The main function of cognitive radio is to exploit “spectrum holes” or “white spaces” to address the challenge of the low utilization of radio resources. Dynamic spectrum allocation, whose significant functions are to ensure that cognitive users access the available frequency and bandwidth to communicate in an opportunistic manner and to minimize the interference between primary and secondary users, is a key mechanism in cognitive radio networks. Reinforcement learning, which rapidly analyzes the amount of data in a model-free manner, dramatically facilitates the performance of dynamic spectrum allocation in real application scenarios. This paper presents a survey on the state-of-the-art spectrum allocation algorithms based on reinforcement learning techniques in cognitive radio networks. The advantages and disadvantages of each algorithm are analyzed in their specific practical application scenarios. Finally, we discuss open issues in dynamic spectrum allocation that can be topics of future research.
      PubDate: 2018-06-22
      DOI: 10.1007/s10462-018-9639-x
       
  • Clustering ensemble selection considering quality and diversity
    • Authors: Sadr-olah Abbasi; Samad Nejatian; Hamid Parvin; Vahideh Rezaie; Karamolah Bagherifard
      Abstract: It is highly likely that there is a partition that is judged by a stability measure as a bad one while it contains one (or more) high quality cluster(s); and then it is totally neglected. So, inspiring from the evaluation of partitions, researchers turn to define measures for evaluation of clusters. Many stability measures have been proposed such as Normalized Mutual Information to validate a partition. The defined measures are based on Normalized Mutual Information. The drawback of the commonly used approach will be discussed in this paper and a criterion is proposed to assess the association between a cluster and a partition which is called Edited Normalized Mutual Information, ENMI criterion. The ENMI criterion compensates the drawback of the common Normalized Mutual Information (NMI) measure. Also, a clustering ensemble method that is based on aggregating a subset of primary clusters is proposed. The proposed method uses the Average ENMI as fitness measure to select a number of clusters. The clusters that satisfy a predefined threshold of the mentioned measure are selected to participate in the final ensemble. To combine the chosen clusters a set of consensus function methods are employed. One class of the used consensus functions is the co-association based consensus functions. Since the Evidence Accumulation Clustering, EAC, method can’t derive the co-association matrix from a subset of clusters, Extended EAC, EEAC, is employed to construct the co-association matrix from the chosen subset of clusters. The second class of the used consensus functions is based on hyper graph partitioning algorithms. The other class of the used consensus functions considers the chosen clusters as a new feature space and uses a simple clustering algorithm to extract the consensus partitioning. The empirical studies show that the proposed method outperforms other well-known ensembles.
      PubDate: 2018-06-21
      DOI: 10.1007/s10462-018-9642-2
       
  • A survey of machine learning techniques for food sales prediction
    • Authors: Grigorios Tsoumakas
      Abstract: Food sales prediction is concerned with estimating future sales of companies in the food industry, such as supermarkets, groceries, restaurants, bakeries and patisseries. Accurate short-term sales prediction allows companies to minimize stocked and expired products inside stores and at the same time avoid missing sales. This paper reviews existing machine learning approaches for food sales prediction. It discusses important design decisions of a data analyst working on food sales prediction, such as the temporal granularity of sales data, the input variables to use for predicting sales and the representation of the sales output variable. In addition, it reviews machine learning algorithms that have been applied to food sales prediction and appropriate measures for evaluating their accuracy. Finally, it discusses the main challenges and opportunities for applied machine learning in the domain of food sales prediction.
      PubDate: 2018-06-14
      DOI: 10.1007/s10462-018-9637-z
       
  • Scene analysis and search using local features and support vector machine
           for effective content-based image retrieval
    • Authors: Uzma Sharif; Zahid Mehmood; Toqeer Mahmood; Muhammad Arshad Javid; Amjad Rehman; Tanzila Saba
      Abstract: Despite broad investigation in content-based image retrieval (CBIR), issue to lessen the semantic gap between high-level semantics and local attributes of the image is still an important issue. The local attributes of an image such as shape, color, and texture are not sufficient for effective CBIR. Visual similarity is a principal step in CBIR and in the baseline approach. In this article, we introduce a novel approach, which relies on the fusion of visual words of scale-invariant feature transform (SIFT) and binary robust invariant scalable keypoints (BRISK) descriptors based on the visual-bag-of-words approach. The two local feature descriptors are chosen as their fusion adds complementary improvement to CBIR. The SIFT descriptor is capable of detecting objects robustly under cluttering due to its invariance to scale, rotation, noise, and illumination variance. However, SIFT descriptor does not perform well at low illumination or poorly localized keypoints within an image. Due to this reason, the discriminative power of the SIFT descriptor is lost during the quantization process, which also reduces the performance of CBIR. However, the BRISK descriptor provides scale and rotation-invariant scale-space, high quality and adaptive performance in classification based applications. It also performs better at poorly localized keypoints along the edges of an object within an image as compared to the SIFT descriptor. The suggested approach based on the fusion of visual words achieves effective results on the Corel-1K, Corel-1.5K, Corel-5K, and Caltech-256 image repositories as equated to the feature fusion of both descriptors and latest CBIR approaches with the surplus assistances of scalability and fast indexing.
      PubDate: 2018-06-13
      DOI: 10.1007/s10462-018-9636-0
       
  • Recent studies on optimisation method of Grey Wolf Optimiser (GWO): a
           review (2014–2017)
    • Authors: N. M. Hatta; Azlan Mohd Zain; Roselina Sallehuddin; Z. Shayfull; Yusliza Yusoff
      Abstract: Today, finding a viable solution for any real world problem focusing on combinatorial of problems is a crucial task. However, using optimisation techniques, a viable best solution for a specific problem can be obtained, developed and solved despite the existing limitations of the implemented technique. Furthermore, population based optimisation techniques are now a current interest and has spawned many new and improved techniques to rectify many engineering problems. One of these methods is the Grey Wolf Optimiser (GWO), which resembles the grey wolf’s leadership hierarchy and its hunting behavior in nature. The GWO adopts the hierarchical nature of grey wolfs and lists the best solution as alpha, followed by beta and delta in descending order. Additionally, its hunting technique of tracking, encircling and attacking are also modeled mathematically to find the best optimised solution. This paper presents the results from an extensive study of 83 published papers from previous studies related to GWO in various applications such as parameter tuning, economy dispatch problem, and cost estimating to name a few. A discussion on the properties of GWO algorithm and how it minimises the different problems in the different applications is presented, as well as an analysis on the research trend of GWO optimisation technique in various applications from year 2014 to 2017. Based on the literatures, it was observed that GWO has the ability to solve single and multi-objective problems efficiently due to its good local search criteria that performs exceptionally well for different problems and solutions.
      PubDate: 2018-05-22
      DOI: 10.1007/s10462-018-9634-2
       
  • Neonatal intensive care decision support systems using artificial
           intelligence techniques: a systematic review
    • Authors: Jaleh Shoshtarian Malak; Hojjat Zeraati; Fatemeh Sadat Nayeri; Reza Safdari; Azimeh Danesh Shahraki
      Abstract: A neonatal intensive care unit (NICU) provides critical services to preterm and high-risk infants. Over the years, many tools and techniques have been introduced to support the clinical decisions made by specialists in the NICU. This study systematically reviewed the different technologies used in neonatal decision support systems (DSS), including cognitive analysis, artificial neural networks, data mining techniques, multi-agent systems, and highlighted their role in patient diagnosis, prognosis, monitoring, and healthcare management. Articles on NICU DSS were surveyed, Searches were based on the PubMed, Science Direct, and IEEE databases and only English articles published after 1990 were included. The overall search strategy was to retrieve articles that included terms that were related to “NICU Decision Support Systems” or “Artificial Intelligence” and “Neonatal”. Different methods and artificial intelligence techniques used in NICU decision support systems were assessed and related outcomes, variables, methods and performance measures was reported and discussed. Because of the dynamic, heterogeneous, and real-time environment of the NICU, the processes and medical rules that are followed within a NICU are complicated, and the data records that are produced are complex and frequent. Therefore, a single tool or technology could not cover all the needs of a NICU. However, it is important to examine and deploy new temporal data mining approaches and system architectures, such as multi-agent systems, services, and sensors, to provide integrated real-time solutions for NICU.
      PubDate: 2018-05-22
      DOI: 10.1007/s10462-018-9635-1
       
  • A comprehensive review of recent advances on deep vision systems
    • Authors: Qaisar Abbas; Mostafa E. A. Ibrahim; M. Arfan Jaffar
      Abstract: Real-time video objects detection, tracking, and recognition are challenging issues due to the real-time processing requirements of the machine learning algorithms. In recent years, video processing is performed by deep learning (DL) based techniques that achieve higher accuracy but require higher computations cost. This paper presents a recent survey of the state-of-the-art DL platforms and architectures used for deep vision systems. It highlights the contributions and challenges from over numerous research studies. In particular, this paper first describes the architecture of various DL models such as AutoEncoders, deep Boltzmann machines, convolution neural networks, recurrent neural networks and deep residual learning. Next, deep real-time video objects detection, tracking and recognition studies are highlighted to illustrate the key trends in terms of cost of computation, number of layers and the accuracy of results. Finally, the paper discusses the challenges of applying DL for real-time video processing and draw some directions for the future of DL algorithms.
      PubDate: 2018-05-11
      DOI: 10.1007/s10462-018-9633-3
       
  • Ontologies’ mappings validation and annotation enrichment through
           tagging
    • Authors: Peter Ochieng; Swaib Kyanda
      Abstract: Pay as you go ontology matching, the technique of first executing an automatic matching tool and then engaging users to improve the quality of an alignment produced by the tool is gaining popularity. Most of the existing techniques employ a single user to validate mappings by annotating them using terms from a controlled set such as “correct” or “incorrect”. This single user based approach of validating mappings using a controlled set of vocabulary is restrictive. First, the use of controlled vocabulary does not maximize the user’s effort since it restrains him/her from adding more meaning to the concepts participating in low-quality mappings using his/her own terms. Secondly, a single user approach of validating a wide range of mappings is error prone since even the most experienced user may not be familiar with all subtopics contained in the input ontologies. We demonstrate in this research that through tagging of concepts participating in mappings flagged as low-quality, we can achieve both mappings’ validation and ontology’s metadata enrichment by adding quality annotations to the ontology.
      PubDate: 2018-05-09
      DOI: 10.1007/s10462-018-9632-4
       
  • Artificial intelligence test: a case study of intelligent vehicles
    • Authors: Li Li; Yi-Lun Lin; Nan-Ning Zheng; Fei-Yue Wang; Yuehu Liu; Dongpu Cao; Kunfeng Wang; Wu-Ling Huang
      Abstract: To meet the urgent requirement of reliable artificial intelligence applications, we discuss the tight link between artificial intelligence and intelligence test in this paper. We highlight the role of tasks in intelligence test for all kinds of artificial intelligence. We explain the necessity and difficulty of describing tasks for intelligence test, checking all the tasks that may encounter in intelligence test, designing simulation-based test, and setting appropriate test performance evaluation indices. As an example, we present how to design reliable intelligence test for intelligent vehicles. Finally, we discuss the future research directions of intelligence test.
      PubDate: 2018-04-12
      DOI: 10.1007/s10462-018-9631-5
       
  • Comparison of artificial neural networks, fuzzy logic and neuro fuzzy for
           predicting optimization of building thermal consumption: a survey
    • Authors: Zahra Pezeshki; Sayyed Majid Mazinani
      Abstract: Data Mining (DM) is a useful technique to discover useful patterns which lead to large searches. This method offers a reliable treatment of all developmental phases from problem and data understanding through data preprocessing to deployment of the results. DM plays an important role in energy efficiency. The construction industry has numerous sources information to compare and turn them into beneficial information. Artificial neural networks (ANN), fuzzy logic (FL) and neuro fuzzy (NF) are used techniques. Although the ANN and FL have many advantages, they also have certain defects. NF enjoys the advantages of both ANN and FL. In this paper, by comparing these techniques present in articles from 2009 to 2017, we have introduced four advantages for NF technique and indicated that the second advantage has been paid less attention other ones. The results reveal that the NF method is more successful than FL and ANN for predicting the thermal efficiency of buildings. However, NF with a learning phase proves to be computationally heavy and time-consuming, especially when the number of rules, the antecedents and the model delays are high. As a result, the proposed method, using nonlinear neural Model Predictive Controllers, is the best answer to thermal control strategies.
      PubDate: 2018-04-04
      DOI: 10.1007/s10462-018-9630-6
       
 
 
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