Jianyong Duan

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Traditional text categorization is usually a topic-based task, but a subtle demand on information retrieval is to distinguish between positive and negative view on text topic. In this paper, a new method is explored to solve this problem. Firstly, a batch of Concerned Concepts in the researched domain is predefined. Secondly, the special knowledge(More)
This paper proposes a new approach for Multi-word Expression (MWE)extraction on the motivation of gene sequence alignment because textual sequence is similar to gene sequence in pattern analysis. Theory of Longest Common Subse-quence (LCS) originates from computer science and has been established as affine gap model in Bioinformatics. We perform this(More)
This paper presents a language modeling approach to the sentiment detection problem. It captures the subtle information in text processing to character the semantic orientation of documents as " thumb up " (positive) or " thumb down " (negative). To handle this problem, we propose an idea to estimate both the positive and negative language models from(More)
In this paper, we present a weakly supervised learning approach for spoken language understanding in domain-specific dialogue systems. We model the task of spoken language understanding as a successive classification problem. The first classifier (topic classifier) is used to identify the topic of an input utterance. With the restriction of the recognized(More)