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Vocabulary mismatch avoidance techniques
, K. Sola, C.B. Sai Reddy, M.V. Rakesh Kumar, P. Harsha Vardhan
Published in International Journal of Scientific and Technology Research
Volume: 9
Issue: 4
Pages: 2585 - 2594
With the advancement of the technology, information is ubiquitously present, in order to deal with the extraction of required information from the existing data need of information retrieval systems are becoming more prominent. Newer and most efficient methods of extracting information are needed. This makes IR more demanding in the field of NLP. Data recovery is a procedure of acquiring data assets that are pertinent to data required from a gathering of those assets. Every person has their own requirements, these requirements are filled by using Information retrieval systems. Basically, an IR system [1] processes a query input and gives the required output. And processing such query is the most difficult task in IR systems. This leads to many problems such as ambiguity, vocabulary mismatch due to polysemy and synonymy. We discuss about solutions for the above problems using methods such as query expansion, stemming and full-text indexing. Query expansion match the given input query with additional documents by expanding it to find synonyms, find semantic relatability, spelling errors and finds the desired output result. Indexing is used to increase the efficiency of an IR system. It clusters the words in a query based on the various distance measures. This survey paper deals about various methods created by different researchers. © 2020 IJSTR.
About the journal
JournalInternational Journal of Scientific and Technology Research
PublisherInternational Journal of Scientific and Technology Research