Context-Aware Lexicon-Based Semantic Similarity of Text

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The company, Messagepoint, has a cloud-based software platform that provides services for**businesses to enable easy communication with their customers. Examples of this type of communication include simple text messages on customer billing information and complete letter inserts that accompany communication between a business and its customers. The company-specific problem is the comparison of text messages in multiple languages for meaning similarity. Lexicon-based similarity algorithms have shown to work well in the context of word matching when exploring the semantic similarity space along word-relation hierarchies. However, these word-focused algorithms, are not very effective when computing semantic similarity for a larger set of words (such as sentences or paragraphs). Natural Language Processing methods will be integrated into the company's platform in order to generate a shallow semantic representation of the text messages generated by the company's software. This shallow semantic analysis will provide representations of the messages that can be compared for similarity of meaning.