-
Sanfilippo, M.; Yang, S.; Fichman, P.: Trolling here, there, and everywhere : perceptions of trolling behaviors in context (2017)
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- Journal of the Association for Information Science and Technology. 68(2017) no.10, S.2313-2327
-
Bernier-Colborne, G.: Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor (2014)
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- Pages
- S.57-62
-
Deuschel, T.; Heuss, T.; Humm, B.: ¬Die Medienplattform : ein System für gerichtete und ungerichtete semantische Suchen (2015)
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- Information - Wissenschaft und Praxis. 66(2015) H.4, S.201-206
-
Darányi, S.; Wittek, P.: Demonstrating conceptual dynamics in an evolving text collection (2013)
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- Journal of the American Society for Information Science and Technology. 64(2013) no.12, S.2564-2572
-
Oh, K.E.; Joo, S.; Jeong, E.-J.: Online consumer health information organization : users' perspectives on faceted navigation (2015)
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- Knowledge organization. 42(2015) no.3, S.176-186
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Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016)
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- Information processing and management. 52(2016) no.5, S.923-948
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Adhikari, A.; Dutta, B.; Dutta, A.; Mondal, D.; Singh, S.: ¬An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology (2018)
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- Journal of the Association for Information Science and Technology. 69(2018) no.8, S.1023-1034
-
Green, R.: See-also relationships in the Dewey Decimal Classification (2011)
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- Knowledge organization. 38(2011) no.4, S.335-341
-
Colace, F.; Santo, M. De; Greco, L.; Napoletano, P.: Weighted word pairs for query expansion (2015)
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- Information processing and management. 51(2015) no.1, S.179-193
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Atanassova, I.; Bertin, M.: Semantic facets for scientific information retrieval (2014)
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- Pages
- S.108-113
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Moreira, W.; Martínez-Ávila, D.: Concept relationships in knowledge organization systems : elements for analysis and common research among fields (2018)
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- Cataloging and classification quarterly. 56(2018) no.1, S.19-39
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Hazrina, S.; Sharef, N.M.; Ibrahim, H.; Murad, M.A.A.; Noah, S.A.M.: Review on the advancements of disambiguation in semantic question answering system (2017)
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- Abstract
- Ambiguity is a potential problem in any semantic question answering (SQA) system due to the nature of idiosyncrasy in composing natural language (NL) question and semantic resources. Thus, disambiguation of SQA systems is a field of ongoing research. Ambiguity occurs in SQA because a word or a sentence can have more than one meaning or multiple words in the same language can share the same meaning. Therefore, an SQA system needs disambiguation solutions to select the correct meaning when the linguistic triples matched with multiple KB concepts, and enumerate similar words especially when linguistic triples do not match with any KB concept. The latest development in this field is a solution for SQA systems that is able to process a complex NL question while accessing open-domain data from linked open data (LOD). The contributions in this paper include (1) formulating an SQA conceptual framework based on an in-depth study of existing SQA processes; (2) identifying the ambiguity types, specifically in English based on an interdisciplinary literature review; (3) highlighting the ambiguity types that had been resolved by the previous SQA studies; and (4) analysing the results of the existing SQA disambiguation solutions, the complexity of NL question processing, and the complexity of data retrieval from KB(s) or LOD. The results of this review demonstrated that out of thirteen types of ambiguity identified in the literature, only six types had been successfully resolved by the previous studies. Efforts to improve the disambiguation are in progress for the remaining unresolved ambiguity types to improve the accuracy of the formulated answers by the SQA system. The remaining ambiguity types are potentially resolved in the identified SQA process based on ambiguity scenarios elaborated in this paper. The results of this review also demonstrated that most existing research on SQA systems have treated the processing of the NL question complexity separate from the processing of the KB structure complexity.
- Source
- Information processing and management. 53(2017) no.1, S.52-69
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Huang, L.; Milne, D.; Frank, E.; Witten, I.H.: Learning a concept-based document similarity measure (2012)
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- Journal of the American Society for Information Science and Technology. 63(2012) no.8, S.1593-1608
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Narock, T.; Zhou, L.; Yoon, V.: Semantic similarity of ontology instances using polarity mining (2013)
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- Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.416-427
-
Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011)
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- Pages
- S.111-121
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Zhang, W.; Yoshida, T.; Tang, X.: ¬A comparative study of TF*IDF, LSI and multi-words for text classification (2011)
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- Source
- Expert-systems with applications. 38(2011) no.3, S.2758-2765
-
Wang, Z.; Khoo, C.S.G.; Chaudhry, A.S.: Evaluation of the navigation effectiveness of an organizational taxonomy built on a general classification scheme and domain thesauri (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.948-963
-
Bräscher, M.: Semantic relations in knowledge organization systems (2014)
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- Knowledge organization. 41(2014) no.2, S.175-180
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Arenas, M.; Cuenca Grau, B.; Kharlamov, E.; Marciuska, S.; Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data (2014)
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-
Colace, F.; Santo, M. de; Greco, L.; Napoletano, P.: Improving relevance feedback-based query expansion by the use of a weighted word pairs approach (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2223-2234
