Difference between revisions of "Exploiting Wikipedia Api for Hindi-English Cross-Language Information Retrieval"
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| − | '''Exploiting Wikipedia Api for Hindi-English Cross-Language Information Retrieval''' - scientific work related to Wikipedia quality published in 2016, written by Vijay Kumar Sharma and Namita Mittal. | + | '''Exploiting Wikipedia Api for Hindi-English Cross-Language Information Retrieval''' - scientific work related to [[Wikipedia quality]] published in 2016, written by [[Vijay Kumar Sharma]] and [[Namita Mittal]]. |
== Overview == | == Overview == | ||
| − | Abstract The rapidly increasing demographics of the internet population and the abundance of multilingual content on the web increased the communication in multiple languages. Most of the people use their regional languages to express their needs and the language diversity becomes a great barrier. Cross-Language Information Retrieval (CLIR) provides a solution for that language barrier which allows a user to ask a query in the native language and get the relevant documents in the different language. In this paper, authors proposed a Wikipedia API based query translation approach. Queries are tokenized and multi-words query terms are created using N-gram technique. Wikipedia title and inter-wiki link features are exploited for query translation. Target language documents are retrieved using vector space retrieval model and BM25 retrieval algorithm. Experiment results shows that the proposed approach achieves better results without exploiting any language resources. | + | Abstract The rapidly increasing demographics of the internet population and the abundance of [[multilingual]] content on the web increased the communication in [[multiple languages]]. Most of the people use their regional languages to express their needs and the language diversity becomes a great barrier. Cross-Language Information Retrieval (CLIR) provides a solution for that language barrier which allows a user to ask a query in the native language and get the relevant documents in the [[different language]]. In this paper, authors proposed a [[Wikipedia]] API based query translation approach. Queries are tokenized and multi-words query terms are created using N-gram technique. Wikipedia title and inter-wiki link [[features]] are exploited for query translation. Target language documents are retrieved using vector space retrieval model and BM25 retrieval algorithm. Experiment results shows that the proposed approach achieves better results without exploiting any language resources. |
Revision as of 08:42, 9 May 2020
Exploiting Wikipedia Api for Hindi-English Cross-Language Information Retrieval - scientific work related to Wikipedia quality published in 2016, written by Vijay Kumar Sharma and Namita Mittal.
Overview
Abstract The rapidly increasing demographics of the internet population and the abundance of multilingual content on the web increased the communication in multiple languages. Most of the people use their regional languages to express their needs and the language diversity becomes a great barrier. Cross-Language Information Retrieval (CLIR) provides a solution for that language barrier which allows a user to ask a query in the native language and get the relevant documents in the different language. In this paper, authors proposed a Wikipedia API based query translation approach. Queries are tokenized and multi-words query terms are created using N-gram technique. Wikipedia title and inter-wiki link features are exploited for query translation. Target language documents are retrieved using vector space retrieval model and BM25 retrieval algorithm. Experiment results shows that the proposed approach achieves better results without exploiting any language resources.
