Query Formulation for Heuristic Retrieval in Obfuscated and Translated Partially Derived Text

Kumar, Aarti; Das, Sujoy

doi:10.1633/jistap.2015.3.1.2

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…For news stories proper nouns form the pivot as the whole story revolves around these. Also, these are never affected even if the text is translated to another language (Aarti Kumar and Sujoy Das, 2015) with the only difference that a transliterated version appears if the translated text uses another script. Queries are formulated in Hindi using dictionary based approach.…”

Section: Pre-retrieval or Heuristic Retrievalmentioning

confidence: 99%

Dealing with Relevance Ranking in Cross-Lingual Cross-Script Text Reuse

Kumar

Das

2016

International Journal of Information Retrieval Research

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Proliferation of multilingual content on the web has paved way for text reuse to get cross-lingual and also cross script. Identifying cross language text reuse becomes tougher if one considers cross-script less resourced languages. This paper focuses on identifying text reuse between English-Hindi news articles and improving their relevance ranking using two phases (i) Heuristic retrieval phase for reducing search space and (ii) post processing phase for improving the relevance ranking. Dictionary based strategy of Cross-Language Information Retrieval is used for heuristic retrieval and Parse Feature Vector Model (PFVS) is proposed for post processing to improve the relevance ranking. The application of this model has been successful in tackling the obfuscation problems of synonymy, hyponymy, hypernymy, antonym, sentence addition/ deletion and word inflection. Instead of using traditional approaches, Parse Feature Vectors have been explored to detect the reused documents and as per the knowledge of the authors it is a novel contribution with regards to these two language pairs.

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Section: Pre-retrieval or Heuristic Retrievalmentioning

confidence: 99%