Latent Semantic Indexing based Intelligent Information Retrieval System for Digital Libraries
نویسندگان
چکیده
منابع مشابه
Latent Semantic Indexing based Intelligent Information Retrieval System for Digital Libraries
To the information retrieval research community, a digital library can be viewed as an extended information retrieval system. The primary goal of an information retrieval system is to retrieve all the relevant documents, which are relevant to the user query. Disparities between the vocabulary of the system’s authors and that of their users pose difficulties when information is processed without...
متن کاملOn the Performance of Latent Semantic Indexing based Information Retrieval
Conventional vector-based Information Retrieval (IR) models: Vector Space Model (VSM) and Generalized Vector Space Model (GVSM) represents documents and queries as vectors in a multidimensional space. This high dimensional data places great demands on computing resources. To overcome these problems, Latent Semantic Indexing (LSI), a variant of VSM, projects the documents into a lower dimensiona...
متن کاملDowndating the Latent Semantic Indexing Model for Conceptual Information Retrieval
Due to the growth of large data collections, information retrieval or database searching is of vital importance. Lexical matching techniques may retrieve irrelevant or inaccurate results because of synonyms and polysemous words, so effective concept-based techniques are needed. One such technique is latent semantic indexing (LSI) which uses a vector-space approach by identifying documents whose...
متن کاملOntology based Semantic Indexing Approach for Information Retrieval System
This paper shows how the gap between the texts based web pages and the Resource Descriptive Framework based pages of the semantic web can be bridged by ontologies. Most traditional search engines use indexes that are engineered at the syntactical level and come back hits based mostly on straightforward string comparisons or use the static keyword based indexing. However, the indexes don't conta...
متن کاملUsing latent semantic indexing for morph-based spoken document retrieval
Previously, phone-based and word-based approaches have been used for spoken document retrieval. The former suffers from high error rates and the latter from limited vocabulary of the recognizer. Our method relies on unlimited vocabulary continuous speech recognizer that uses morpheme-like units discovered in an unsupervised manner. The morpheme-like units, or “morphs” for short, have been succe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computing and Information Technology
سال: 2006
ISSN: 1330-1136
DOI: 10.2498/cit.1000730