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Journal Cover   Journal of Information Science
  [SJR: 1.008]   [H-I: 40]   [868 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  [759 journals]
  • A linguistic approach for determining the topics of Spanish Twitter
           messages
    • Authors: Vilares, D; Alonso, M. A, Gomez-Rodriguez, C.
      Pages: 127 - 145
      Abstract: The vast number of opinions and reviews provided in Twitter is helpful in order to make interesting findings about a given industry, but given the huge number of messages published every day, it is important to detect the relevant ones. In this respect, the Twitter search functionality is not a practical tool when we want to poll messages dealing with a given set of general topics. This article presents an approach to classify Twitter messages into various topics. We tackle the problem from a linguistic angle, taking into account part-of-speech, syntactic and semantic information, showing how language processing techniques should be adapted to deal with the informal language present in Twitter messages. The TASS 2013 General corpus, a collection of tweets that has been specifically annotated to perform text analytics tasks, is used as the dataset in our evaluation framework. We carry out a wide range of experiments to determine which kinds of linguistic information have the greatest impact on this task and how they should be combined in order to obtain the best-performing system. The results lead us to conclude that relating features by means of contextual information adds complementary knowledge over pure lexical models, making it possible to outperform them on standard metrics for multilabel classification tasks.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514561652
      Issue No: Vol. 41, No. 2 (2015)
       
  • Towards improving XML search by using structure clustering technique
    • Authors: Shalabi, R; Elfatatry, A.
      Pages: 146 - 166
      Abstract: Searching large XML repositories is a challenging research problem. The application of clustering on a large repository before performing a search enhances the search process significantly. Clustering reduces a search space into smaller XML collections that can be better searched. In this work, we present an enhanced XML clustering by structure method. Also, we introduce a new representation of XML structure that keeps all characteristics of XML structure without summarization. Then, we perform a benchmark comparison between the search results of our improved method to SAXON and Qizx XML XQuery processors. The comparison focuses on search processing time and accuracy of the results using different sizes of datasets for both homogeneous and heterogeneous XML documents. The attained results show better accuracy at the same level of performance.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514560523
      Issue No: Vol. 41, No. 2 (2015)
       
  • Accurate similarity index based on the contributions of paths and end
           nodes for link prediction
    • Authors: Li, L; Qian, L, Cheng, J, Ma, M, Chen, X.
      Pages: 167 - 177
      Abstract: Link prediction whose intent is to discover the likelihood of the existence of a link between two disconnected nodes is an important task in complex network analysis. To perform this task, a similarity-based algorithm that employs the similarities of nodes to find links is a very popular solution. However, when calculating the similarity between two nodes, most of the similarity-based algorithms only focus on the contributions of paths connecting these two nodes but ignore the influences of these two nodes themselves. Therefore, their results are not accurate enough. In this paper, a novel similarity index, called Scop, is proposed for link prediction. By directly defining the contributions of paths to their end nodes and the contributions of end nodes themselves, Scop not only distinguishes the contributions of different paths but also integrates the contributions of end nodes. Hence, Scop can obtain better performance on accuracy. Experiments on 10 networks compared with six baselines indicate that Scop is remarkably better than others.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514560121
      Issue No: Vol. 41, No. 2 (2015)
       
  • Keyword-based mobile semantic search using mobile ontology
    • Authors: Shin, S; Ko, J, Eom, S, Song, M, Shin, D.-H, Lee, K.-H.
      Pages: 178 - 196
      Abstract: A large volume of mobile data is being generated and shared among mobile devices such as smartphones. Most of the mobile platforms provide a user with a keyword-based full text search (FTS) in order to search for mobile data. However, FTS only returns the data corresponding to the keywords given by users as results without considering a user’s query intention. To overcome this limitation, we propose a semantically enhanced keyword-based search method. Although there are various semantic search techniques, it is hard to apply existing methods to mobile devices just as they are. This is caused by the characteristics of mobile devices such as isolated database structures and limited computing resources. To enable semantic search on mobile devices, we also propose a lightweight mobile ontology. Experimental results from the prototype implementation of the proposed method show that the proposed method provides a better user experience than the conventional FTS and returns accurate search results in an acceptable response time.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514560669
      Issue No: Vol. 41, No. 2 (2015)
       
  • Study of dynamics of structured knowledge: Qualitative analysis of
           different mapping approaches
    • Authors: Osinska, V; Bala, P.
      Pages: 197 - 208
      Abstract: The authors compared three methods of mapping, considering the maps as a visual interface for the exploration of scientific articles related to computer science. Data were classified according to the original Computing Classification System (CCS) classification and co-categories were used for similarity metrics calculation. The authors’ approach based on MDS was enriched by algorithm mapping to spherical topology. Three other methods were based on VOS, VxOrd and SOM mapping techniques. Visualization of the classified collection was done for three different decades. Tracking the changes in visualization patterns, the authors sought the method that would reveal the real evolution of the CCS scheme, which is still being updated by the editorial board. Comparative analysis is based on qualitative methods. Changes in those properties over two decades were evaluated for the benefit of the authors’ method of mapping. The qualitative analysis shows clustering of proper categories and overlapping of other ones in the authors’ approach, which corresponds to the current changes in the classification scheme and computer science literature.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514559897
      Issue No: Vol. 41, No. 2 (2015)
       
  • Discovering expansion entities for keyword-based entity search in linked
           data
    • Authors: Zong, N; Lee, S, Kim, H.-G.
      Pages: 209 - 227
      Abstract: There is an inherent rift between the characteristics of Web of documents and the Web of data – the latter is enriched with semantic properties that are not present in the former. This creates a formidable challenge for entity search in the era of Linked Data, requiring a new method that leverages on such features. Query expansion, used in keyword-based search, improves search quality by enhancing a query with terms. Existing query-expansion methods, statistical- and lexical-based approaches, are inadequate for linked data in two ways: (a) term-to-term co-occurrence, used in the statistical-based approach, cannot find satisfactory expansions in internal corpus (SPO triples) or external corpus (Web of documents); and (b) lexical incomparability between ontologies (or thesauri) as reference knowledge and linked data renders tenuous the possibility of creating lexically sound expanded queries. The study introduces a framework to expand keyword queries with expansion entities for keyword-based entity search in linked data. The framework offers two structures, star-shaped and multi-shaped RDF graphs (documents), to model the entities in linked data for indexing and search, and an algorithm called PFC for expansion entities by which to expand a given query. PFC obtains expansion entities by measuring a global importance (PageRank and entity–document Frequency) and a local importance (Centrality) of the candidates extracted from the returned RDF documents of the entity search. Our experiments illustrate that PFC improves search results by approximately 7%. This study also includes suggestions on how to glean important link types for extracting candidate expansion entities, as well as identifying properties of these entities by which to expand the query.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514562704
      Issue No: Vol. 41, No. 2 (2015)
       
  • Is seeking health information online different from seeking general
           information online?
    • Authors: Kim; Y.-M.
      Pages: 228 - 241
      Abstract: Increasing use of the Internet for health information delivery has created considerable discussion among digital divide scholars (i.e. how online information delivery benefits those individuals in higher socioeconomic brackets more than their counterparts). Because it is health information, we need to integrate how patients seek out online information. This study included patients’ information-seeking behaviour along with digital divide scholars’ constructs (i.e. literacy and computer skills). Using 1617 observations from the 2010 Pew Internet and American Life Project, this study found that individuals with a significant number of health problems, who are likely to be in a lower income bracket, are proactive online health information seekers; however, they are less likely to search general information. This finding adds value to existing research revealing that usefulness, which has been overlooked in online health information seeking, is important and should be a part of the research model.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514561669
      Issue No: Vol. 41, No. 2 (2015)
       
  • Transforming XML documents to OWL ontologies: A survey
    • Authors: Hacherouf, M; Bahloul, S. N, Cruz, C.
      Pages: 242 - 259
      Abstract: The aims of XML data conversion to ontologies are the indexing, integration and enrichment of existing ontologies with knowledge acquired from these sources. The contribution of this paper consists in providing a classification of the approaches used for the conversion of XML documents into OWL ontologies. This classification underlines the usage profile of each conversion method, providing a clear description of the advantages and drawbacks belonging to each method. Hence, this paper focuses on two main processes, which are ontology enrichment and ontology population using XML data. Ontology enrichment is related to the schema of the ontology (TBox), and ontology population is related to an individual (Abox). In addition, the ontologies described in these methods are based on formal languages of the Semantic Web such as OWL (Ontology Web Language) or RDF (Resource Description Framework). These languages are formal because the semantics are formally defined and take advantage of the Description Logics. In contrast, XML data sources are without formal semantics. The XML language is used to store, export and share data between processes able to process the specific data structure. However, even if the semantics is not explicitly expressed, data structure contains the universe of discourse by using a qualified vocabulary regarding a consensual agreement. In order to formalize this semantics, the OWL language provides rich logical constraints. Therefore, these logical constraints are evolved in the transformation of XML documents into OWL documents, allowing the enrichment and the population of the target ontology. To design such a transformation, the current research field establishes connections between OWL constructs (classes, predicates, simple or complex data types, etc.) and XML constructs (elements, attributes, element lists, etc.). Two different approaches for the transformation process are exposed. The instance approaches are based on XML documents without any schema associated. The validation approaches are based on the XML schema and document validated by the associated schema. The second approaches benefit from the schema definition to provide automated transformations with logic constraints. Both approaches are discussed in the text.
      PubDate: 2015-03-09T04:10:16-07:00
      DOI: 10.1177/0165551514565972
      Issue No: Vol. 41, No. 2 (2015)
       
 
 
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