Hindi - English based cross language Information Retrieval system for Allahabad Museum

Pemawat, Vivek; Saund, Abhinav; Agrawal, Anupam

doi:10.1109/icsip.2010.5697460

Cited by 5 publications

(2 citation statements)

References 5 publications

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“…With this method Query Expansion proved to be effective. Another paper published by Vivek Pemawat, Abhinav Saund and Anupam Agrawal in year 2010 tiltled "Hindi -English Based Cross Language Information Retrieval System for Allahabad Museum" [3]. The paper talks about the system developed for CLIR.…”

Section: Methodsmentioning

confidence: 99%

Cross Language Information Retrieval using Selective Documents Technique and Query Expansion

Agrawal¹

2018

Helix

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This paper is devoted to a new method that uses combined technique of pseudo relevance feedback and co-occurring term technique for query expansion to improve cross language information retrieval along with selective document technique to reduce search space. The base is an Information Retrieval (IR) system which uses cosine similarity technique to retrieve and rank documents and a multilingual module using dictionary based translation where the tf-idf values are calculated and stored in inverted index which is term based index. The threshold value is used as a selection medium for documents which reduces the search space of index reducing the overall time for retrieval. A Query Expansion (QE) module is added in to the said system. The aim is to use QE to overcome the limitations of dictionary based translation, and to retrieve more relevant results. The system is validated with several measures, which shows the difference in the result before expansion and after expansion.

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Section: Methodsmentioning

confidence: 99%

Cross Language Information Retrieval using Selective Documents Technique and Query Expansion

Agrawal¹

2018

Helix

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“…Then the postings list of the term "Cross" would be the list [1,2], meaning the term "Cross" appears in documents with IDs 1 and 2. Similarly the postings list of the term "Issues" would be [2,3], and for the term "Ranking" the postings list would be [1]. We may also want to keep extra information in the index such as the number of different documents that the term appears in or the number of occurrences of the term in the whole collection etc.…”

Section: Inverted Indexmentioning

confidence: 99%

Improving Performance of Hindi-English based Cross Language Information Retrieval using Selective Documents Technique and Query Expansion

2016

IJSR

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This paper introduces a system for cross language information retrieval where selective term technique and query expansion will be combined to improve the retrieval of more relevant documents. The document and query processing is done using the techniques of tf-idf and cosine similarity for retrieval. Threshold value is decided to retrieve the documents relevant to query. Later a pseudo Relevance technique will be applied to further expand the query and improve relevance in future.

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An improved approach to English-Hindi based Cross Language Information Retrieval system

Katta

Arora

2015

2015 Eighth International Conference on Contemporary Computing (IC3)

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Hindi - English based cross language Information Retrieval system for Allahabad Museum

Cited by 5 publications

References 5 publications

Cross Language Information Retrieval using Selective Documents Technique and Query Expansion

Cross Language Information Retrieval using Selective Documents Technique and Query Expansion

Improving Performance of Hindi-English based Cross Language Information Retrieval using Selective Documents Technique and Query Expansion

An improved approach to English-Hindi based Cross Language Information Retrieval system

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