1. A computer-implemented method for interpreting text segments based on word sense, the method comprising: parsing a text segment to generate one or more text-based words and related syntactic information; mapping, via a processor, each of the one or more text-based words to at least one concept included in a database and based on a semantic network that includes the at least one concept and one or more relevance ratings associated with the at least one concept, wherein each concept included in the semantic network is associated with a meaning and at least one word; generating a plurality of topics based on the mappings and the syntactic information, wherein each topic includes one or more of the concepts included in the semantic network; for each topic included in the plurality of topics, calculating a topic relevance rating between the topic and at least another topic included in the plurality of topics based on the relevance ratings between the one or more concepts included in the topic and one or more concepts included in the another topic; ranking the plurality of topics based on the topic relevance ratings to generate a ranked topic list; and outputting an element for display based on the ranked topic list.
1. A computer-implemented method for interpreting text segments based on word sense, the method comprising: parsing a text segment to generate one or more text-based words and related syntactic information; mapping, via a processor, each of the one or more text-based words to at least one concept included in a database and based on a semantic network that includes the at least one concept and one or more relevance ratings associated with the at least one concept, wherein each concept included in the semantic network is associated with a meaning and at least one word; generating a plurality of topics based on the mappings and the syntactic information, wherein each topic includes one or more of the concepts included in the semantic network; for each topic included in the plurality of topics, calculating a topic relevance rating between the topic and at least another topic included in the plurality of topics based on the relevance ratings between the one or more concepts included in the topic and one or more concepts included in the another topic; ranking the plurality of topics based on the topic relevance ratings to generate a ranked topic list; and outputting an element for display based on the ranked topic list. 3. The computer-implemented method of claim 1 , wherein mapping each of the one or more text-based words comprises performing one or more word sense disambiguation operations.