Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

Factors associated with successful answering of clinical questions using an information retrieval system*

Objectives: Despite the growing use of online databases by clinicians, there has been very little research documenting how effectively they are used. This study assessed the ability of medical and nurse-practitioner students to answer clinical questions using an information retrieval system. It also attempted to identify the demographic, experience, cognitive, personality, search mechanics, and user-satisfaction factors associated with successful use of a retrieval system.

Roadside Safety Library - library information retrieval system (LIRS). Volume 1: user's manual. Final report.

Turner-Fairbank Highway Research Center, McLean, Va.

Roadside Safety Library - Library Information Retrieval System (LIRS). Volume 2: programmers' and operators' manual. Final report.

Turner-Fairbank Highway Research Center, McLean, Va.

A probabilistic model for a specialized information retrieval system /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

An analysis of rotational storage access scheduling in a multiprogrammed information retrieval system /

Thesis--University of Illinois at Urbana-Champaign.

Description of an experimental on-line, minicomputer-based information retrieval system /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

Evaluation of selected features of the Eureka full-text information retrieval system /

Vita.

An experimental information retrieval system /

Bibliography: p. 114.

A thesaurus feature for the EUREKA information retrieval system /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

A unique word-scanning facility for the Eureka full-text information retrieval system /

Thesis (M.S.)--University of Illinois at Urbana-Champaign.

Users' guide to the Solid Waste Information Retrieval System thesaurus /

"Originally issued in 1973 as open-file report SW-104of."

English-Malayalam Cross-Lingual Information Retrieval – an Experience

This paper describes about an English-Malayalam Cross-Lingual Information Retrieval system. The system retrieves Malayalam documents in response to query given in English or Malayalam. Thus monolingual information retrieval is also supported in this system. Malayalam is one of the most prominent regional languages of Indian subcontinent. It is spoken by more than 37 million people and is the native language of Kerala state in India. Since we neither had any full-fledged online bilingual dictionary nor any parallel corpora to build the statistical lexicon, we used a bilingual dictionary developed in house for translation. Other language specific resources like Malayalam stemmer, Malayalam morphological root analyzer etc developed in house were used in this work

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.