Semantic Aspect Retrieval for Encyclopedia

with the development of web 2.0, more and more people contribute their knowledge to the internet. many general and domain-specific online encyclopedia resources become available, and they are valuable for many natural language processing (nlp) applications, such as summarization and question-answering. we propose a novel encyclopedia-specific method to retrieve passages which are semantically related to a short query (usually comprises of only one word/phrase) from a given article in the encyclopedia. the method captures the expression word features and categorical word features in the surrounding snippets of the aspect words by setting up massive hybrid language models. these local models outperform the global models such as lsa and esa in our task.