@article{MAKHILLJEAS201712814349, title = {Semantic Similarity for Search Engine Enhancement}, journal = {Journal of Engineering and Applied Sciences}, volume = {12}, number = {8}, pages = {1979-1982}, year = {2017}, issn = {1816-949x}, doi = {jeasci.2017.1979.1982}, url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.1979.1982}, author = {Detty,Lintang,Reni,Dessy and}, keywords = {e-Commerce,search engine,semantic similarity,query rewriting,website}, abstract = {Now a days we still found the search results of search engines on websites that are not in accordance with the wishes of user and only provide the information that the keyword search could not be found. For e-Commerce website, this can cause the website would be left by users/prospective buyers so based on that, this research is to increase search results on search engine from e-Commerce websites using semantic similarity and query rewriting. Semantic similarity used is engineering calculations by Leacock and Chodrow. The illustrations in this research is to provide a snapshot query rewriting to make a new query results from semantic similarity and the test method is carried out on a prototype e-Commerce website as well as provides results that the search engine on the website after added semantic similarity approach and query rewriting that provide a better search results.} }