許安順

The rapid advance in information technologies and the fast development of the Internet have realized expedient and transparent information sharing. However, the following problems often occur due to the fast accumulation of information, when searching for content via Internet. (1) Conventional keyword-based search methods can only make partial concept comparisons. Revisions on query are always required before getting appropriate contents. (2) As contents provided by typical queries are less than that of general texts, difficulties in determining search topics and matching appropriate contents occurred very often due to lack of information. (3) Semantics variations may cause concept ambiguity and lead to the low accuracy in information retrieval. To address the aforementioned issues, this study developed a semantic- awareness mechanism for information retrieval. By conducting “semantic retrieval and determination” and “query content semantic extension” and “semantic pattern search”, the mechanism provides more accurate results as compared to traditional keyword based methods. Through semantic analysis, latent semantics mining, and semantic comparison, the issues caused by semantic ambiguity can be resolved and thus improve efficiency and accuracy of information retrieval.