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Gauch, S.; Chandramouli, A.; Ranganathan, S.: Training a hierarchical classifier using inter document relationships (2009)
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- Abstract
- Text classifiers automatically classify documents into appropriate concepts for different applications. Most classification approaches use flat classifiers that treat each concept as independent, even when the concept space is hierarchically structured. In contrast, hierarchical text classification exploits the structural relationships between the concepts. In this article, we explore the effectiveness of hierarchical classification for a large concept hierarchy. Since the quality of the classification is dependent on the quality and quantity of the training data, we evaluate the use of documents selected from subconcepts to address the sparseness of training data for the top-level classifiers and the use of document relationships to identify the most representative training documents. By selecting training documents using structural and similarity relationships, we achieve a statistically significant improvement of 39.8% (from 54.5-76.2%) in the accuracy of the hierarchical classifier over that of the flat classifier for a large, three-level concept hierarchy.
- Date
- 23. 2.2009 18:34:38
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Haverkamp, D.S.; Gauch, S.: Intelligent information agents : review and challenges for distributed information sources (1998)
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- Abstract
- Presents an overview of intelligent software agents in information retrieval, including an explanation of agents and agent architecture, and presents several agent systems. Distinguishes between agents as individual entities, whose properties and characteristics are described separately, and agent systems as collections of agents utilised for information retrieval tasks, which are discussed in terms of individual implementations
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Gauch, S.; Chong, M.K.: Automatic word similarity detection for TREC 4 query expansion (1996)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
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Gauch, S.; Wang, J.: Corpus analysis for TREC 5 query expansion (1997)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
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Gauch, S.: Intelligent information retrieval : an introduction (1992)
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- Abstract
- Researchers are exploring the application of artificial intelligence techniques to information retrieval with the goal of providing intelligent access to online information. This article surveys several such systems to show what is possible in the lab today, and what may be possible in the library or office of tomorrow. Systems incorporating user modeling, natural language understanding, and expert systems technology are presented.
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Gauch, S.; Smith, J.B.: ¬An expert system for automatic query reformation (1993)
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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
