Word meanings are central to the semantic interpretation of texts. Although much work to date has focused on statistical approaches that often ignore the explicit understanding of the text, recent research work has begun to challenge this simplification, demonstrating that semantic interpretation is indeed essential for a number of language processing applications.
The key observation underlying this CAREER project is that word meaning distinctions differ from one lexical resource to another and that the optimality of word meaning representations should be dictated by the target application. The project is exploring rich and flexible word meaning representations that combine the benefits of multiple monolingual and cross-lingual lexical resources and that can be adapted to the context and to the target application. In particular, the multilingual nature of these representations allows for an effective exploitation of the knowledge and resources available in different languages. The project also explores the role played by these word meaning representations and the corresponding monolingual and cross-lingual knowledge sources in several natural language processing tasks including lexical substitution, word and text translation, and text-to-text semantic similarity.
Another aim of the project is to integrate natural language processing into educational applications, and explore the use of the word meaning interpretation models to build a comprehension-assistant tool for students of English as a second language (ESL) and English as a foreign language (EFL). The educational program also fosters increased awareness about research in multilingual natural language processing among college, undergraduate, and graduate students, through a college outreach program and a new course on multilingual computational linguistics, as well as increased exposure of students to international experiences through international collaborations.
