Search (43 results, page 2 of 3)

Guerrero-Bote, V.P.; Moya Anegón, F. de; Herrero Solana, V.: Document organization using Kohonen's algorithm (2002) 0.01

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Abstract: The classification of documents from a bibliographic database is a task that is linked to processes of information retrieval based on partial matching. A method is described of vectorizing reference documents from LISA which permits their topological organization using Kohonen's algorithm. As an example a map is generated of 202 documents from LISA, and an analysis is made of the possibilities of this type of neural network with respect to the development of information retrieval systems based on graphical browsing.

Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996) 0.01

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Date: 12. 9.1996 13:56:22

Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996) 0.01

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Source: Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon

Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003) 0.01

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Date: 22. 3.2003 19:27:36

Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.01

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Date: 31. 5.2004 19:22:06

Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.01

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Date: 11. 9.2004 17:32:22

Witschel, H.F.: Global term weights in distributed environments (2008) 0.01

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Date: 1. 8.2008 9:44:22

Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.01

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Date: 16.11.2008 16:22:48

Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.01

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Date: 22. 3.2003 19:30:19

Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995) 0.01

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Date: 22. 2.1996 11:20:06

Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01

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Date: 22. 2.1996 13:14:10

Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01

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Date: 22. 3.2003 19:35:46

Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.01

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Date: 22. 7.2006 16:32:43

Dominich, S.: Mathematical foundations of information retrieval (2001) 0.01

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Date: 22. 3.2008 12:26:32

Baloh, P.; Desouza, K.C.; Hackney, R.: Contextualizing organizational interventions of knowledge management systems : a design science perspectiveA domain analysis (2012) 0.01

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Date: 11. 6.2012 14:22:34

Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013) 0.01

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Date: 22. 3.2013 19:34:49

Efron, M.: Query expansion and dimensionality reduction : Notions of optimality in Rocchio relevance feedback and latent semantic indexing (2008) 0.01
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Abstract

Rocchio relevance feedback and latent semantic indexing (LSI) are well-known extensions of the vector space model for information retrieval (IR). This paper analyzes the statistical relationship between these extensions. The analysis focuses on each method's basis in least-squares optimization. Noting that LSI and Rocchio relevance feedback both alter the vector space model in a way that is in some sense least-squares optimal, we ask: what is the relationship between LSI's and Rocchio's notions of optimality? What does this relationship imply for IR? Using an analytical approach, we argue that Rocchio relevance feedback is optimal if we understand retrieval as a simplified classification problem. On the other hand, LSI's motivation comes to the fore if we understand it as a biased regression technique, where projection onto a low-dimensional orthogonal subspace of the documents reduces model variance.

Zhang, W.; Yoshida, T.; Tang, X.: ¬A comparative study of TF*IDF, LSI and multi-words for text classification (2011) 0.01

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Koumenides, C.L.; Shadbolt, N.R.: Ranking methods for entity-oriented semantic web search (2014) 0.01
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Abstract

This article provides a technical review of semantic search methods used to support text-based search over formal Semantic Web knowledge bases. Our focus is on ranking methods and auxiliary processes explored by existing semantic search systems, outlined within broad areas of classification. We present reflective examples from the literature in some detail, which should appeal to readers interested in a deeper perspective on the various methods and systems implemented in the outlined literature. The presentation covers graph exploration and propagation methods, adaptations of classic probabilistic retrieval models, and query-independent link analysis via flexible extensions to the PageRank algorithm. Future research directions are discussed, including development of more cohesive retrieval models to unlock further potentials and uses, data indexing schemes, integration with user interfaces, and building community consensus for more systematic evaluation and gradual development.
Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014) 0.01
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Abstract

With ever increasing information being available to the end users, search engines have become the most powerful tools for obtaining useful information scattered on the Web. However, it is very common that even most renowned search engines return result sets with not so useful pages to the user. Research on semantic search aims to improve traditional information search and retrieval methods where the basic relevance criteria rely primarily on the presence of query keywords within the returned pages. This work is an attempt to explore different relevancy ranking approaches based on semantics which are considered appropriate for the retrieval of relevant information. In this paper, various pilot projects and their corresponding outcomes have been investigated based on methodologies adopted and their most distinctive characteristics towards ranking. An overview of selected approaches and their comparison by means of the classification criteria has been presented. With the help of this comparison, some common concepts and outstanding features have been identified.

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