Search (257 results, page 2 of 13)

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Abstract

The challenge of effectively bringing specific, relevant information from the global sea of data to our fingertips, has become an increasingly difficult one. Discusses how the online information industry, founded on Boolean search systems, may be evolving to take advantage of other methods, such as 'term weighting', 'relevance ranking' and 'query by example'

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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

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Abstract

Genetic-based evolutionary learning algorithms, such as genetic algorithms (GAs) and genetic programming (GP), have been applied to information retrieval (IR) since the 1980s. Recently, GP has been applied to a new IR taskdiscovery of ranking functions for Web search-and has achieved very promising results. However, in our prior research, only one fitness function has been used for GP-based learning. It is unclear how other fitness functions may affect ranking function discovery for Web search, especially since it is weIl known that choosing a proper fitness function is very important for the effectiveness and efficiency of evolutionary algorithms. In this article, we report our experience in contrasting different fitness function designs an GP-based learning using a very large Web corpus. Our results indicate that the design of fitness functions is instrumental in performance improvement. We also give recommendations an the design of fitness functions for genetic-based information retrieval experiments.

Date

31. 5.2004 19:22:06

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Abstract

The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.

Date

16.11.2008 16:22:48

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Unfamiliarity with search tactics creates difficulties for many users of online retrieval systems. User observations indicate that even experienced searchers use vocabulary incorrectly and rarely reformulate their queries. To address these problems, an expert system for online search assistance was developed. This prototype automatically reformulates queries to improve the search results, and ranks the retrieved passages to speed the identification of relevant information. User's search performance using the expert system was compared with their search performance using an online thesaurus. The following conclusions were reached: (1) the expert system significantly reduced the number of queries necessary to find relevant passages compared with the user searching alone or with the thesaurus. (2) The expert system produced marginally significant improvements in precision compared with the user searching on their own. There was no significant difference in the recall achieved by the three system configurations. (3) Overall, the expert system ranked relevant passages above irrelevant passages

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Abstract

In most commercial online systems, the retrieval system is based on the Boolean model and its inverted file organization. Since the investment in these systems is so great and changing them could be economically unfeasible, this article suggests a new ranking scheme especially adapted for hypertext environments in order to produce more effective retrieval results and yet maintain the effectiveness of the investment made to date in the Boolean model. To select the retrieved documents, the suggested ranking strategy uses multiple sources of document content evidence. The proposed scheme integrates both the information provided by the index and query terms, and the inherent relationships between documents such as bibliographic references or hypertext links. We will demonstrate that our scheme represents an integration of both subject and citation indexing, and results in a significant imporvement over classical ranking schemes uses in hybrid Boolean systems, while preserving its efficiency. Moreover, through knowing the nearest neighbor and the hypertext links which constitute additional sources of evidence, our strategy will take them into account in order to further improve retrieval effectiveness and to provide 'good' starting points for browsing in a hypertext or hypermedia environement

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Abstract

Summarises the results to date of a continuing programme of research at Sheffield Univ. to investigate the use of nearest-neighbour retrieval algorithms for full text searching. Given a natural language query statement, the research methods result in a ranking of the paragraphs comprising a full text document in order of decreasing similarity with the query, where the similarity for each paragraph is determined by the number of keyword stems that it has in common with the query

Source

Online review. 15(1991) nos.3/4, S.173-190

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Abstract

Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing an theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept an the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based an semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.

Date

22. 3.2003 19:35:46

Footnote

Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

The Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders an a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS-systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.

Footnote

Teil eines Themenheftes: "Web retrieval and mining: A machine learning perspective"

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

Describes an alternative method of representation for documents and queries in information retrieval systems to the 2 most common methods: free text, natural language representation and controlled language representation. The alternative method combines the advantage of both traditional approaches and overcomes the difficulties associated with each. The scheme was developed for use with Longman's Dictionary of Contemporary English and uses a computerized version of the dictionary for the automatic generation of summary level semantic representations of each document and query. The system tags each word in a document with the appropriate Subject Field Code (SFC) from the dictionary and the SFCs are summed and normalized to produce a weighted, fixed length vector of the SFC. The search system matches the query SFC vector to the document SFC vectors in the database. The documents are then ranked on the basis of their vector's similarity to the query

Source

Proceedings of the 14th National Online Meeting 1993, New York, 4-6 May 1993. Ed.: M.E. Williams

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Abstract

As more online databases are integrated into digital libraries, the issue of quality control of the data becomes increasingly important, especially as it relates to the effective retrieval of information. Authority work, the need to discover and reconcile variant forms of strings in bibliographical entries, will become more critical in the future. Spelling variants, misspellings, and transliteration differences will all increase the difficulty of retrieving information. We investigate a number of approximate string matching techniques that have traditionally been used to help with this problem. We then introduce the notion of approximate word matching and show how it can be used to improve detection and categorization of variant forms. We demonstrate the utility of these approaches using data from the Astrophysics Data System and show how we can reduce the human effort involved in the creation of authority files

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Date

22. 2.1996 13:14:10

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Date

22. 7.2006 16:32:43

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

A new challenge, accessing multiple relevant entities, arises from the availability of linked heterogeneous data. In this article, we address more specifically the problem of accessing relevant entities, such as publications and authors within a bibliographic network, given an information need. We propose a novel algorithm, called BibRank, that estimates a joint relevance of documents and authors within a bibliographic network. This model ranks each type of entity using a score propagation algorithm with respect to the query topic and the structure of the underlying bi-type information entity network. Evidence sources, namely content-based and network-based scores, are both used to estimate the topical similarity between connected entities. For this purpose, authorship relationships are analyzed through a language model-based score on the one hand and on the other hand, non topically related entities of the same type are detected through marginal citations. The article reports the results of experiments using the Bibrank algorithm for an information retrieval task. The CiteSeerX bibliographic data set forms the basis for the topical query automatic generation and evaluation. We show that a statistically significant improvement over closely related ranking models is achieved.

Date

22. 3.2013 19:34:49

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Abstract

In this chapter we review the main concepts and data structures used in information retrieval, and we classify information retrieval related algorithms

Source

Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates

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Source

Information storage and retrieval. 6(1971), S.417-435

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Abstract

Presents a comprehensive approach to automatic organization and hybrid navigation of text databases. An organizing stage builds a particular lattice representation of the data, through text indexing followed by lattice clustering of the indexed texts. The lattice representation supports the navigation state of the system, a visual retrieval interface that combines 3 main retrieval strategies: browsing, querying, and bounding. Such a hybrid paradigm permits high flexibility in trading off information exploration and retrieval, and had good retrieval performance. Compares information retrieval using lattice-based hybrid navigation with conventional Boolean querying. Experiments conducted on 2 medium-sized bibliographic databases showed that the performance of lattice retrieval was comparable to or better than Boolean retrieval

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Source

Information retrieval. 3(2000), S.313-338