-
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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- Abstract
- Finding similarity between concepts based on semantics has become a new trend in many applications (e.g., biomedical informatics, natural language processing). Measuring the Semantic Similarity (SS) with higher accuracy is a challenging task. In this context, the Information Content (IC)-based SS measure has gained popularity over the others. The notion of IC evolves from the science of information theory. Information theory has very high potential to characterize the semantics of concepts. Designing an IC-based SS framework comprises (i) an IC calculator, and (ii) an SS calculator. In this article, we propose a generic intrinsic IC-based SS calculator. We also introduce here a new structural aspect of an ontology called DCS (Disjoint Common Subsumers) that plays a significant role in deciding the similarity between two concepts. We evaluated our proposed similarity calculator with the existing intrinsic IC-based similarity calculators, as well as corpora-dependent similarity calculators using several benchmark data sets. The experimental results show that the proposed similarity calculator produces a high correlation with human evaluation over the existing state-of-the-art IC-based similarity calculators.
- Date
- 29. 7.2018 11:40:33
-
Hetzler, B.: Visual analysis and exploration of relationships (2002)
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- Abstract
- Relationships can provide a rich and powerful set of information and can be used to accomplish application goals, such as information retrieval and natural language processing. A growing trend in the information science community is the use of information visualization-taking advantage of people's natural visual capabilities to perceive and understand complex information. This chapter explores how visualization and visual exploration can help users gain insight from known relationships and discover evidence of new relationships not previously anticipated.
-
Brambilla, M.; Ceri, S.: Designing exploratory search applications upon Web data sources (2012)
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- Abstract
- Search is the preferred method to access information in today's computing systems. The Web, accessed through search engines, is universally recognized as the source for answering users' information needs. However, offering a link to a Web page does not cover all information needs. Even simple problems, such as "Which theater offers an at least three-stars action movie in London close to a good Italian restaurant," can only be solved by searching the Web multiple times, e.g., by extracting a list of the recent action movies filtered by ranking, then looking for movie theaters, then looking for Italian restaurants close to them. While search engines hint to useful information, the user's brain is the fundamental platform for information integration. An important trend is the availability of new, specialized data sources-the so-called "long tail" of the Web of data. Such carefully collected and curated data sources can be much more valuable than information currently available in Web pages; however, many sources remain hidden or insulated, in the lack of software solutions for bringing them to surface and making them usable in the search context. A new class of tailor-made systems, designed to satisfy the needs of users with specific aims, will support the publishing and integration of data sources for vertical domains; the user will be able to select sources based on individual or collective trust, and systems will be able to route queries to such sources and to provide easyto-use interfaces for combining them within search strategies, at the same time, rewarding the data source owners for each contribution to effective search. Efforts such as Google's Fusion Tables show that the technology for bringing hidden data sources to surface is feasible.
-
Koopman, B.; Zuccon, G.; Bruza, P.; Sitbon, L.; Lawley, M.: Information retrieval as semantic inference : a graph Inference model applied to medical search (2016)
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- Abstract
- This paper presents a Graph Inference retrieval model that integrates structured knowledge resources, statistical information retrieval methods and inference in a unified framework. Key components of the model are a graph-based representation of the corpus and retrieval driven by an inference mechanism achieved as a traversal over the graph. The model is proposed to tackle the semantic gap problem-the mismatch between the raw data and the way a human being interprets it. We break down the semantic gap problem into five core issues, each requiring a specific type of inference in order to be overcome. Our model and evaluation is applied to the medical domain because search within this domain is particularly challenging and, as we show, often requires inference. In addition, this domain features both structured knowledge resources as well as unstructured text. Our evaluation shows that inference can be effective, retrieving many new relevant documents that are not retrieved by state-of-the-art information retrieval models. We show that many retrieved documents were not pooled by keyword-based search methods, prompting us to perform additional relevance assessment on these new documents. A third of the newly retrieved documents judged were found to be relevant. Our analysis provides a thorough understanding of when and how to apply inference for retrieval, including a categorisation of queries according to the effect of inference. The inference mechanism promoted recall by retrieving new relevant documents not found by previous keyword-based approaches. In addition, it promoted precision by an effective reranking of documents. When inference is used, performance gains can generally be expected on hard queries. However, inference should not be applied universally: for easy, unambiguous queries and queries with few relevant documents, inference did adversely affect effectiveness. These conclusions reflect the fact that for retrieval as inference to be effective, a careful balancing act is involved. Finally, although the Graph Inference model is developed and applied to medical search, it is a general retrieval model applicable to other areas such as web search, where an emerging research trend is to utilise structured knowledge resources for more effective semantic search.
-
Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:17:40
-
Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
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- Date
- 30. 3.2001 13:32:22
-
Ross, J.: ¬A new way of information retrieval : 3-D indexing and concept mapping (2000)
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- Date
- 25. 2.1997 10:29:16
-
Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-enhanced search interfaces (2002)
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- Date
- 18. 5.2002 17:29:00
-
Shiri, A.A.; Revie, C.: ¬The effects of topic complexity and familiarity on cognitive and physical moves in a thesaurus-enhanced search environment (2003)
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- Source
- Journal of information science. 29(2003) no.6, S.517-
-
Stojanovic, N.: On the query refinement in the ontology-based searching for information (2005)
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- Date
- 5. 4.1996 15:29:15
-
Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016)
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- Date
- 1. 2.2016 18:25:22
-
Kozikowski, P. et al.: Support of part-whole relations in query answering (2016)
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- Date
- 1. 2.2016 18:25:22
-
Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
Sacco, G.M.: Dynamic taxonomies and guided searches (2006)
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- Date
- 22. 7.2006 17:56:22
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Jarvelin, K.: ¬A deductive data model for thesaurus navigation and query expansion (1996)
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- Date
- 2. 3.1997 17:29:07
-
Sacco, G.M.: Accessing multimedia infobases through dynamic taxonomies (2004)
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- Date
- 29. 8.2004 10:15:02
-
Hoppe, T.: Semantische Filterung : ein Werkzeug zur Steigerung der Effizienz im Wissensmanagement (2013)
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- Date
- 29. 9.2015 18:56:44
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Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994)
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- Date
- 30. 3.2001 13:35:22
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Frederichs, A.: Natürlichsprachige Abfrage und 3-D-Visualisierung von Wissenszusammenhängen (2007)
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- Date
- 25.10.2007 9:51:29
- Source
- Wa(h)re Information: 29. Österreichischer Bibliothekartag Bregenz, 19.-23.9.2006. Hrsg.: Harald Weigel
