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Journal Cover Journal of Information Science
  [SJR: 0.629]   [H-I: 47]   [825 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0165-5515 - ISSN (Online) 1741-6485
   Published by Sage Publications Homepage  [853 journals]
  • When time meets information retrieval: Past proposals, current plans and
           future trends
    • Authors: Moulahi, B; Tamine, L, Yahia, S. B.
      Pages: 725 - 747
      Abstract: With the advent of Web search and the large amount of data published on the Web sphere, a tremendous amount of documents become strongly time-dependent. In this respect, the time dimension has been extensively exploited as a highly important relevance criterion to improve the retrieval effectiveness of document ranking models. Thus, a compelling research interest is going on the temporal information retrieval realm, which gives rise to several temporal search applications. In this article, we intend to provide a scrutinizing overview of time-aware information retrieval models. We specifically put the focus on the use of timeliness and its impact on the global value of relevance as well as on the retrieval effectiveness. First, we attempt to motivate the importance of temporal signals, whenever combined with other relevance features, in accounting for document relevance. Then, we review the relevant studies standing at the crossroads of both information retrieval and time according to three common information retrieval aspects: the query level, the document content level and the document ranking model level. We organize the related temporal-based approaches around specific information retrieval tasks and regarding the task at hand, we emphasize the importance of results presentation and particularly timelines to the end user. We also report a set of relevant research trends and avenues that can be explored in the future.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515607277
      Issue No: Vol. 42, No. 6 (2016)
       
  • Exploiting semantics for searching agricultural bibliographic data
    • Authors: Beneventano, D; Bergamaschi, S, Martoglia, R.
      Pages: 748 - 762
      Abstract: Filtering and search mechanisms which permit to identify key bibliographic references are fundamental for researchers. In this paper we propose a fully automatic and semantic method for filtering/searching bibliographic data, which allows users to look for information by specifying simple keyword queries or document queries, i.e. by simply submitting existing documents to the system. The limitations of standard techniques, based on either syntactical text search and on manually assigned descriptors, are overcome by considering the semantics intrinsically associated to the document/query terms; to this aim, we exploit different kinds of external knowledge sources (both general and specific domain dictionaries or thesauri). The proposed techniques have been developed and successfully tested for agricultural bibliographic data, which play a central role to enable researchers and policy makers to retrieve related agricultural and scientific information by using the AGROVOC thesaurus.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515606579
      Issue No: Vol. 42, No. 6 (2016)
       
  • Topic-based content and sentiment analysis of Ebola virus on Twitter and
           in the news
    • Authors: Kim, E. H.-J; Jeong, Y. K, Kim, Y, Kang, K. Y, Song, M.
      Pages: 763 - 781
      Abstract: The present study investigates topic coverage and sentiment dynamics of two different media sources, Twitter and news publications, on the hot health issue of Ebola. We conduct content and sentiment analysis by: (1) applying vocabulary control to collected datasets; (2) employing the n-gram LDA topic modeling technique; (3) adopting entity extraction and entity network; and (4) introducing the concept of topic-based sentiment scores. With the query term ‘Ebola’ or ‘Ebola virus’, we collected 16,189 news articles from 1006 different publications and 7,106,297 tweets with the Twitter stream API. The experiments indicate that topic coverage of Twitter is narrower and more blurry than that of the news media. In terms of sentiment dynamics, the life span and variance of sentiment on Twitter is shorter and smaller than in the news. In addition, we observe that news articles focus more on event-related entities such as person, organization and location, whereas Twitter covers more time-oriented entities. Based on the results, we report on the characteristics of Twitter and news media as two distinct news outlets in terms of content coverage and sentiment dynamics.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515608733
      Issue No: Vol. 42, No. 6 (2016)
       
  • Arabic tweets sentiment analysis - a hybrid scheme
    • Authors: Aldayel, H. K; Azmi, A. M.
      Pages: 782 - 797
      Abstract: The fact that people freely express their opinions and ideas in no more than 140 characters makes Twitter one of the most prevalent social networking websites in the world. Being popular in Saudi Arabia, we believe that tweets are a good source to capture the public’s sentiment, especially since the country is in a fractious region. Going over the challenges and the difficulties that the Arabic tweets present – using Saudi Arabia as a basis – we propose our solution. A typical problem is the practice of tweeting in dialectical Arabic. Based on our observation we recommend a hybrid approach that combines semantic orientation and machine learning techniques. Through this approach, the lexical-based classifier will label the training data, a time-consuming task often prepared manually. The output of the lexical classifier will be used as training data for the SVM machine learning classifier. The experiments show that our hybrid approach improved the F-measure of the lexical classifier by 5.76% while the accuracy jumped by 16.41%, achieving an overall F-measure and accuracy of 84 and 84.01% respectively.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515610513
      Issue No: Vol. 42, No. 6 (2016)
       
  • A hybrid ontology-based information extraction system
    • Authors: Gutierrez, F; Dou, D, Fickas, S, Wimalasuriya, D, Zong, H.
      Pages: 798 - 820
      Abstract: Information Extraction is the process of automatically obtaining knowledge from plain text. Because of the ambiguity of written natural language, Information Extraction is a difficult task. Ontology-based Information Extraction (OBIE) reduces this complexity by including contextual information in the form of a domain ontology. The ontology provides guidance to the extraction process by providing concepts and relationships about the domain. However, OBIE systems have not been widely adopted because of the difficulties in deployment and maintenance. The Ontology-based Components for Information Extraction (OBCIE) architecture has been proposed as a form to encourage the adoption of OBIE by promoting reusability through modularity. In this paper, we propose two orthogonal extensions to OBCIE that allow the construction of hybrid OBIE systems with higher extraction accuracy and a new functionality. The first extension utilizes OBCIE modularity to integrate different types of implementation into one extraction system, producing a more accurate extraction. For each concept or relationship in the ontology, we can select the best implementation for extraction, or we can combine both implementations under an ensemble learning schema. The second extension is a novel ontology-based error detection mechanism. Following a heuristic approach, we can identify sentences that are logically inconsistent with the domain ontology. Because the implementation strategy for the extraction of a concept is independent of the functionality of the extraction, we can design a hybrid OBIE system with concepts utilizing different implementation strategies for extracting correct or incorrect sentences. Our evaluation shows that, in the implementation extension, our proposed method is more accurate in terms of correctness and completeness of the extraction. Moreover, our error detection method can identify incorrect statements with a high accuracy.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515610989
      Issue No: Vol. 42, No. 6 (2016)
       
  • Information as causality: An approach to a general theory of information
    • Authors: Luo, T; Pan, Y.
      Pages: 821 - 832
      Abstract: Although various approaches have been proposed throughout history, information, as one of the most fundamental elements in the world, does not have a general definition or theory that is acceptable to all disciplines. The biggest challenge is the unification of objective and subjective views, because they represent very different characteristics of information which are difficult to integrate into a single framework. We argue that the key to bridging the gap between objective and subjective views of information is a proper understanding of intelligence, because it gives rise to subjective experiences and assigns meaning to things. The purpose of this research is to explore possibilities and implications of applying neuroscience theory in the discussion of information. By incorporating the memory–prediction framework of intelligence developed by Jeff Hawkins, we propose causality to be the general definition of information, and the combination of ‘Physical Representations of Mental Patterns’ and ‘Physical Representations of Physical Patterns’ to be the restricted definition in social contexts. With both general and restricted definitions clarified, we then discuss a few cases of information use and the implications of our approach.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515612662
      Issue No: Vol. 42, No. 6 (2016)
       
  • A qualitative investigation of users discovery, access, and organization
           of video games as information objects
    • Authors: Lee, J. H; Clarke, R. I, Rossi, S.
      Pages: 833 - 850
      Abstract: Video games are popular consumer products as well as research subjects, yet little exists about how players and other stakeholders find video games and what information they need to select, acquire and play video games. With the aim of better understanding people’s game-related information needs and behaviour, we conducted 56 semi-structured interviews with users who find, play, purchase, collect and recommend video games. Participants included gamers, parents, collectors, industry professionals, librarians, educators and scholars. From this user data, we derive and discuss key design implications for video game information systems: designing for target user populations, enabling recommendations based on appeals, offering multiple automatic organization options and providing relationship-based, user-generated, subject and visual metadata. We anticipate this work will contribute to building future video game information systems with new and improved access to games.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515618594
      Issue No: Vol. 42, No. 6 (2016)
       
  • A semantic-based approach for querying linked data using natural language
    • Authors: Paredes-Valverde, M. A; Valencia-Garcia, R, Rodriguez-Garcia, M. A, Colomo-Palacios, R, Alor-Hernandez, G.
      Pages: 851 - 862
      Abstract: The semantic Web aims to provide to Web information with a well-defined meaning and make it understandable not only by humans but also by computers, thus allowing the automation, integration and reuse of high-quality information across different applications. However, current information retrieval mechanisms for semantic knowledge bases are intended to be only used by expert users. In this work, we propose a natural language interface that allows non-expert users the access to this kind of information through formulating queries in natural language. The present approach uses a domain-independent ontology model to represent the question’s structure and context. Also, this model allows determination of the answer type expected by the user based on a proposed question classification. To prove the effectiveness of our approach, we have conducted an evaluation in the music domain using LinkedBrainz, an effort to provide the MusicBrainz information as structured data on the Web by means of Semantic Web technologies. Our proposal obtained encouraging results based on the F-measure metric, ranging from 0.74 to 0.82 for a corpus of questions generated by a group of real-world end users.
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551515616311
      Issue No: Vol. 42, No. 6 (2016)
       
  • List of reviewers for Volume 42
    • Pages: 863 - 864
      PubDate: 2016-11-25T07:50:10-08:00
      DOI: 10.1177/0165551516664048
      Issue No: Vol. 42, No. 6 (2016)
       
 
 
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