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Full-Text Articles in Physical Sciences and Mathematics
Improving Library Searches Using Word-Correlation Factors And Folksonomies, Maria Soledad Pera
Improving Library Searches Using Word-Correlation Factors And Folksonomies, Maria Soledad Pera
Theses and Dissertations
Libraries, private and public, offer valuable resources to library patrons; however, formulating library queries to retrieve relevant results can be difficult. This occurs because when using a library catalog for library searches, patrons often do not know the exact keywords to be included in a query that match the rigid subject terms (chosen by the Library of Congress) or terms in other fields of a desired library catalog record. These improperly formulated queries often translate into a high percentage of failed searches that retrieve irrelevant results or no results at all. This explains why frustrated library patrons nowadays rely on …
An Analysis Of Document Retrieval And Clustering Using An Effective Semantic Distance Measure, Nathan Scott Davis
An Analysis Of Document Retrieval And Clustering Using An Effective Semantic Distance Measure, Nathan Scott Davis
Theses and Dissertations
As large amounts of digital information become more and more accessible, the ability to effectively find relevant information is increasingly important. Search engines have historically performed well at finding relevant information by relying primarily on lexical and word based measures. Similarly, standard approaches to organizing and categorizing large amounts of textual information have previously relied on lexical and word based measures to perform grouping or classification tasks. Quite often, however, these processes take place without respect to semantics, or word meanings. This is perhaps due to the fact that the idea of meaningful similarity is naturally qualitative, and thus difficult …
Using Vagueness Measures To Re-Rank Documents Retrieved By A Fuzzy Set Information Retrieval Model, Stephen Lynn, Yiu-Kai D. Ng
Using Vagueness Measures To Re-Rank Documents Retrieved By A Fuzzy Set Information Retrieval Model, Stephen Lynn, Yiu-Kai D. Ng
Faculty Publications
Traditional information retrieval (IR) systems evaluate user queries and retrieve/rank documents based on matching keywords in user queries with words in documents. These exact word-matching and ranking approaches ignore too many relevant documents that do not contain the exact keywords as specified in a user query. Instead of considering these traditional approaches, we propose to retrieve documents using a fuzzy set IR model and rank retrieved documents for any vague query using the “vagueness score” of the documents based on the word senses as defined in WordNet. Using the vagueness scores, we rank the most highest “relevant” documents of a …
An Infrastructure For Performance Measurement And Comparison Of Information Retrieval Solutions, Gary Saunders
An Infrastructure For Performance Measurement And Comparison Of Information Retrieval Solutions, Gary Saunders
Theses and Dissertations
The amount of information available on both public and private networks continues to grow at a phenomenal rate. This information is contained within a wide variety of objects, including documents, e-mail archives, medical records, manuals, pictures and music. To be of any value, this data must be easily searchable and accessible. Information Retrieval (IR) is concerned with the ability to find and gain access to relevant information. As electronic data repositories continue to proliferate, so too, grows the variety of methods used to locate and access the information contained therein. Similarly, the introduction of innovative retrieval strategies—and the optimization of …