Search (47 results, page 3 of 3)

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Date

20. 1.2015 18:30:22

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Source

International classification. 13(1986), S.18-23

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Abstract

Accessing useful information from a complex database requires knowledge of the structure of the database and an understanding of the methods of information retrieval. A means of overcoming this knowledge barrier to the use of narrow domain databases is proposed in which the user is required to enter only a series of terms which identify the required material. Describes a method which classifies terms according to their meaning in the context of the database and which uses this classification to access and execute models of code stored in the database to effect retrieval. Presents an implementation of the method using a database of technical information on the nature and use of fungicides. Initial results of trials with potential users indicate that the system can produce relevant resposes to queries expressed in this style. Since the code modules are part of the database, extensions may be easily implemented to handle most queries which users are likely to pose

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Source

Cataloging and classification quarterly. 44(2007) nos.3/4, S.197-211

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Abstract

So far, methods for ellipsis and anaphor resolution have been developed and the effects of anaphor resolution have been analyzed in the context of statistical information retrieval of scientific abstracts. No significant improvements has been observed. Analyzes the effects of ellipsis and anaphor resolution on proximity searching in a full text database. Anaphora and ellipsis are classified on the basis of the type of their correlates / antecedents rather than, as traditional, on the basis of their own linguistic type. The classification differentiates proper names and common nouns of basic words, compound words, and phrases. The study was carried out in a newspaper article database containing 55.000 full text articles. A set of 154 keyword pairs in different categories was created. Human resolution of keyword ellipsis and anaphora was performed to identify sentences and paragraphs which would match proximity searches after resolution. Findings indicate that ellipsis and anaphor resolution is most relevant for proper name phrases and only marginal in the other keyword categories. Therefore the recall effect of restricted resolution of proper name phrases only was analyzed for keyword pairs containing at least 1 proper name phrase. Findings indicate a recall increase of 38.2% in sentence searches, and 28.8% in paragraph searches when proper name ellipsis were resolved. The recall increase was 17.6% sentence searches, and 19.8% in paragraph searches when proper name anaphora were resolved. Some simple and computationally justifiable resolution method might be developed only for proper name phrases to support keyword based full text information retrieval. Discusses elements of such a method

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Abstract

Semantic annotations have to satisfy quality constraints to be useful for digital libraries, which is particularly challenging on large and diverse datasets. Confidence scores of multi-label classification methods typically refer only to the relevance of particular subjects, disregarding indicators of insufficient content representation at the document-level. Therefore, we propose a novel approach that detects documents rather than concepts where quality criteria are met. Our approach uses a deep, multi-layered regression architecture, which comprises a variety of content-based indicators. We evaluated multiple configurations using text collections from law and economics, where the available content is restricted to very short texts. Notably, we demonstrate that the proposed quality estimation technique can determine subsets of the previously unseen data where considerable gains in document-level recall can be achieved, while upholding precision at the same time. Hence, the approach effectively performs a filtering that ensures high data quality standards in operative information retrieval systems.

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Date

22. 3.2009 18:48:28