A METHOD AND SYSTEM FOR MONITORING SOCIAL MEDIA AND ANALYZING TEXT TO AUTOMATE CLASSIFICATION OF USER POSTS USING A FACET BASED RELEVANCE ASSESSMENT MODEL

摘要

A social media monitoring and text analysis method for automated classification of user posts on the web, using a facet based relevance assessment model, comprise a semantic indexing server, which builds a faceted classification index of text objects, and a query server, which receives and analyzes the user's query. A query thus processed is then sent from the query server to the semantic indexing server through an interface in order to perform a search in the faceted classification index. The search system and method further comprise a result handler, which provides the user with a search result set comprising a list of unexpected links and a list of result elements. The list of unexpected links corresponds to filters which allow the user to narrow down or refine the original query. The quality of unexpected links depends on identification of the most likely topical area of focus related to the query concepts and corresponding concepts in user posts, and this achieved by ensuring that we measure statistical co¬ occurrence of concepts in user posts, assign weighted scores based on information gain and semantic density, thus establishing a relevant conceptual tag cloud that is used validate topical focus against a set of industry specific taxonomies or ontologies.