| This dissertation addresses the problem about how to apply syntactical information in search.;We first survey the various existing methods, focusing on the dilemma that obtaining high accuracy results usually sacrifice the response time. We then propose a novel information retrieval framework to combine keyword-based search and search based on syntactical information. In particular, we design a sequential structure LSC (Language Sequential Component) to encode syntactical information. Given a sentence, LSC provides a bridge from its syntactical representation and semantic meaning. We also propose a learning algorithm to obtain the LSC from a training set, a classification algorithm to find the relevant LSC from a user query to interpret the intentions of the user, and a search framework (called Semantic Search Engine) to incorporate syntactical information into a keyword based search system. Our experiments show the Semantic Search Engine outperforms the keyword-based approach significantly. |
