TY - GEN
T1 - A methodology to measure the semantic similarity between words based on the formal concept analysis
AU - Jeong, Yewon
AU - Yoon, Yiyeon
AU - Jeon, Dongkyu
AU - Cho, Youngsang
AU - Kim, Wooju
PY - 2014
Y1 - 2014
N2 - Recently, web users feel difficult to find the desired information on the internet despite a lot of useful information since it takes more time and effort to find it. In order to solve this problem, the query expansion is considered as a new alternative. It is the process of reformulating a query to improve retrieval performance in information retrieval operations. Although there are a few techniques of query expansion, synonym identification is one of them. Therefore, this paper proposes the method to measure the semantic similarity between two words by using the keyword-based web documents. The formal concept analysis and our proposed expansion algorithm are used to estimate the similarity between two words. To evaluate the performance of our method, we conducted two experiments. As the results, the average of similarity between synonym pairs is much higher than random pairs. Also, our method shows the remarkable performance in comparison with other method. Therefore, the suggested method in this paper has the contribution to find the synonym among a lot of candidate words.
AB - Recently, web users feel difficult to find the desired information on the internet despite a lot of useful information since it takes more time and effort to find it. In order to solve this problem, the query expansion is considered as a new alternative. It is the process of reformulating a query to improve retrieval performance in information retrieval operations. Although there are a few techniques of query expansion, synonym identification is one of them. Therefore, this paper proposes the method to measure the semantic similarity between two words by using the keyword-based web documents. The formal concept analysis and our proposed expansion algorithm are used to estimate the similarity between two words. To evaluate the performance of our method, we conducted two experiments. As the results, the average of similarity between synonym pairs is much higher than random pairs. Also, our method shows the remarkable performance in comparison with other method. Therefore, the suggested method in this paper has the contribution to find the synonym among a lot of candidate words.
UR - http://www.scopus.com/inward/record.url?scp=84902380329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902380329&partnerID=8YFLogxK
U2 - 10.5220/0004855603130321
DO - 10.5220/0004855603130321
M3 - Conference contribution
AN - SCOPUS:84902380329
SN - 9789897580246
T3 - WEBIST 2014 - Proceedings of the 10th International Conference on Web Information Systems and Technologies
SP - 313
EP - 321
BT - WEBIST 2014 - Proceedings of the 10th International Conference on Web Information Systems and Technologies
PB - SciTePress
T2 - 10th International Conference on Web Information Systems and Technologies, WEBIST 2014
Y2 - 3 April 2014 through 5 April 2014
ER -