A Query Expansion Using Support Vector Machine (SVM) and Best Matching 25 (BM25)

Muhadi Ramelan

doi:10.29040/ijcis.v5i2.162

A Query Expansion Using Support Vector Machine (SVM) and Best Matching 25 (BM25)

Muhadi Ramelan

Abstract

The information retrieval system needs to be upgraded constantly to improving retrieval performance. Expansion Query is one of the information retrieval methods for retrieve more relevant documents. Several technique expansion queries are synonym expansion, Thesaurus Expansion, and Word Embedding Expansion. This research uses a Support Vector Machine ( SVM ) to get new terms from the corpus. Some people are sometimes confused about what must to write to get the desired document or are too lazy to write a lot of words. In this research, Based on the input query data SVM will search for condition data from the existing corpus so that the data obtained will later become an expansion for the query. Adding additional terms to capture a broader range of relevant documents will retrieve more documents and improve the relevance of search results.

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DOI: https://doi.org/10.29040/ijcis.v5i2.162