This paper reviewed the most recent evaluation criteria methods, which were used in different e-business services. As the dependency on web technology increases, the need to assess the factors associated with website success increases as well. The Internet creates a new business environment, far different from anything that has come before because it lets a company conducts its entire set of business processes and practices online. Web services are being widely deployed throughout business, education, government, and other organizations. Companies seeking to achieve significant benefits through e-business need to create an effective and usable web presence to ensure successful interaction and communication with their employees, partners, and customers. Since the introduction of the first commercial website in 1994, electronic commerce has spread across the globe as a marketing, sales, and communication phenomenon, changing the fact of some business sectors.

In the age of information technology and with the rapid growth of the World Wide Web, the spectacular growth trend in e-business, that has been experienced so far, is expected to continue. The experimental results demonstrated promising performance improvements over classic information retrieval methods utilizing plain lexical matching (e.g., Vector Space Model) and also over state-of-theart semantic similarity retrieval methods utilizing ontologies. SSRM has been applied in retrieval on OHSUMED (a standard TREC collection available on the Web). The most effective semantic similarity method is implemented into SSRM. Building upon semantic similarity, we propose the Semantic Similarity based Retrieval Model (SSRM), a novel information retrieval method capable for discovering similarities between documents containing conceptually similar terms. The most popular semantic similarity methods are implemented and evaluated using WordNet and MeSH.

We investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). Typically, semantic similarity is computed by mapping terms to an ontology and by examining their relationships in that ontology. Semantic Similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms.

Sononym for term