for Journals by Title or ISSN
for Articles by Keywords
help
Followed Journals
Journal you Follow: 0
 
Sign Up to follow journals, search in your chosen journals and, optionally, receive Email Alerts when new issues of your Followed Journals are published.
Already have an account? Sign In to see the journals you follow.
Journal Cover Journal of Information Science
  [SJR: 0.629]   [H-I: 47]   [806 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  [852 journals]
  • QSem: A novel question representation framework for question matching over
           accumulated question-answer data
    • Authors: Hao, T; Qu, Y.
      Pages: 583 - 596
      Abstract: This paper proposes a novel question representation framework to assist automated question answering through reusing accumulated question–answer data. The framework, named QSem, defines three types of question words – question-target words, user-oriented words and irrelevant words, along with semantic patterns, for representing a question. The question word types are semantically labelled by a pre-defined ontology to enrich the semantic representation of questions. The semantic patterns through equivalent pattern linking enhance normal structure matching aiming at improving question matching performance. We trained QSem on 400 randomly selected questions with semantic patterns and obtained optimized parameters. After that, 5000 questions from our system were tested and the precision of question matching was between 0.71 and 0.93 with respect to various generators, indicating the stability of the approach. We further compared our approach with Cosine similarity, WordNet-based semantic similarity and IBM translation model on a standard TREC dataset containing 5536 questions. The results presented that our approach achieved best performance with mean reciprocal rank increased by 7.2% and accuracy increased by 7.5% on average, demonstrating the effectiveness of the approach.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515602457
      Issue No: Vol. 42, No. 5 (2016)
       
  • Topic segmentation using word-level semantic relatedness functions
    • Authors: Ercan, G; Cicekli, I.
      Pages: 597 - 608
      Abstract: Semantic relatedness deals with the problem of measuring how much two words are related to each other. While there is a large body of research for developing new measures, the use of semantic relatedness (SR) measures in topic segmentation has not been explored. In this research the performance of different SR measures is evaluated in the topic segmentation problem. To this end, two topic segmentation algorithms that use the difference in SR of words are introduced. Our results indicate that using an SR measure trained with a general domain corpora achieves better results than topic segmentation algorithms using Wordnet or simple word repetition. Furthermore, when compared with computationally more complex algorithms performing global analysis, our local analysis, enhanced with general domain lexical semantic information, achieves comparable results.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515602460
      Issue No: Vol. 42, No. 5 (2016)
       
  • Exploring collaborative work among graduate students through the C5 model
           of collaboration: A diary study
    • Authors: Shah, C; Leeder, C.
      Pages: 609 - 629
      Abstract: Collaborative work among students, while an important topic of inquiry, needs further treatment as we still lack the knowledge regarding obstacles that students face, the strategies they apply, and the relations among personal and group aspects. This article presents a diary study of 54 master’s students conducting group projects across four semesters. A total of 332 diary entries were analysed using the C5 model of collaboration that incorporates elements of communication, contribution, coordination, cooperation and collaboration. Quantitative and qualitative analyses show how these elements relate to one another for students working on collaborative projects. It was found that face-to-face communication related positively with satisfaction and group dynamics, whereas online chat correlated positively with feedback and closing the gap. Managing scope was perceived to be the most common challenge. The findings suggest the varying affordances and drawbacks of different methods of communication, collaborative work styles and the strategies of group members.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515603322
      Issue No: Vol. 42, No. 5 (2016)
       
  • Applying the semantic web to represent an individuals academic and
           professional background
    • Authors: Teixeira, F; Araujo, G. D, Baptista, R, Araujo, L. V, Pisa, I. T.
      Pages: 630 - 638
      Abstract: The Lattes Platform is a web-based system that brings together the academic, professional and scientific histories of students, teachers, researchers and other professionals linked to scientific and technological careers. The data are entered by users themselves and are the subject of much research and forecasting in relation to how educational resources are directed in Brazil. In this paper, we report our experience in applying the Linked Data principles to this system. We have also demonstrated the potential of federated queries using data from DBPedia.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515605742
      Issue No: Vol. 42, No. 5 (2016)
       
  • Approximate pattern matching with gap constraints
    • Authors: Wu, Y; Tang, Z, Jiang, H, Wu, X.
      Pages: 639 - 658
      Abstract: Pattern matching is a key issue in sequential pattern mining. Many researchers now focus on pattern matching with gap constraints. However, most of these studies involve exact pattern matching problems, a special case of approximate pattern matching and a more challenging task. In this study, we introduce an approximate pattern matching problem with Hamming distance. Its objective is to compute the number of approximate occurrences of pattern P with gap constraints in sequence S under similarity constraint d. We propose an efficient algorithm named Single-rOot Nettree for approximate pattern matchinG with gap constraints (SONG) based on a new non-linear data structure Single-root Nettree to effectively solve the problem. Theoretical analysis and experiments demonstrate an interesting law that the ratio M(P,S,d)/N(P,S,m) approximately follows a binomial distribution, where M(P,S,d) and N(P,S,m) are the numbers of the approximate occurrences whose distances to pattern P are d (0≤d≤m) and no more than m (the length of pattern P), respectively. Experimental results for real biological data validate the efficiency and effectiveness of SONG.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515603286
      Issue No: Vol. 42, No. 5 (2016)
       
  • OLFinder: Finding opinion leaders in online social networks
    • Authors: Aleahmad, A; Karisani, P, Rahgozar, M, Oroumchian, F.
      Pages: 659 - 674
      Abstract: Opinion leaders are the influential people who are able to shape the minds and thoughts of other people in their society. Finding opinion leaders is an important task in various domains ranging from marketing to politics. In this paper, a new effective algorithm for finding opinion leaders in a given domain in online social networks is introduced. The proposed algorithm, named OLFinder, detects the main topics of discussion in a given domain, calculates a competency and a popularity score for each user in the given domain, then calculates a probability for being an opinion leader in that domain by using the competency and the popularity scores and finally ranks the users of the social network based on their probability of being an opinion leader. Our experimental results show that OLFinder outperforms other methods based on precision-recall, average precision and P@N measures.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515605217
      Issue No: Vol. 42, No. 5 (2016)
       
  • Implications of augmented reality in the management of television
           audiovisual information
    • Authors: Caldera-Serrano, J; Leon-Moreno, J.-A.
      Pages: 675 - 680
      Abstract: This document analyses the possibilities offered by augmented reality for exploiting the audiovisual collections of television archives, thereby presenting the idea, which has not been developed by any network, of providing viewers with the material issued and submitted synchronously for broadcasting. By using external elements other than TV sets (tablets, iPads, Smartphones), users can access images from the archive, which have been used to generate the information or programme, contributing also with additional elements that may be of interest. Other contents related to the information provided may be similarly accessed, thus facilitating a real conceptual map of the audiovisual contents of any event. Access may be granted free of charge or by paying a fee. Commercial exploitation is achieved in the form of viewer loyalty by gaining access to additional content and providing greater bi-directionality to the communication between viewers and the media.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515608341
      Issue No: Vol. 42, No. 5 (2016)
       
  • Social informatics as a concept: Widening the discourse
    • Authors: Smutny; Z.
      Pages: 681 - 710
      Abstract: This contribution examines the different concepts known as social informatics that have historically been separate. The paradigm that is preferred worldwide (based on Kling) is well described and often promoted, with a strong base both in the USA and Europe. This article, however, introduces lesser-known paradigms (based on Sokolov and later Ursul) that originated in the era of the USSR and have so far been employed chiefly in post-Soviet countries, including Russia. These paradigms have been neglected in English-written scientific literature, mainly because of the limited number of articles available in English. Other approaches are also introduced and related, which were historically named or classified as social informatics (American, British, Norwegian, Slovenian, German and Japanese). The present article introduces and further discusses the origin, historical development and basic methodological grounding of these approaches. All the approaches are then discussed and their differences as well as their similarities are pointed out. The aim is to create connections across the current generation of researchers, which includes the formation and conceptualization of different approaches and an exploration of possible areas for future cooperation.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515608731
      Issue No: Vol. 42, No. 5 (2016)
       
  • Profiling users with tag networks in diffusion-based personalized
           recommendation
    • Authors: Mao, J; Lu, K, Li, G, Yi, M.
      Pages: 711 - 722
      Abstract: This study explores new ways of tag-based personalized recommendation by relieving the assumption that tags assigned by a user occur independently of each other. The new methods profile users using tag co-occurrence networks, upon which link-based node weighting methods (e.g. PageRank and HITS) are applied to refine the weights of tags. A diffusion process is then performed upon the tag-item bipartite graph to transform the weights of tags into recommendation scores for items. Experiments on three datasets showed improvements of the proposed method over the tag-based collaborative filtering in terms of precision and recall in the datasets with dense user-tag networks and in terms of inter-diversity in all datasets. In addition, the user-tag network is found to be a necessary instrument for the improvements. The findings of this study contribute to more accurate user profiling and personalized recommendations using network theory and have practical implications for tag-based recommendation systems.
      PubDate: 2016-09-05T02:21:50-07:00
      DOI: 10.1177/0165551515603321
      Issue No: Vol. 42, No. 5 (2016)
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016