This work proposes a semi-supervised sentiment classification method which is based on the co-training framework. The proposed method needs to construct three sentiment classifiers. We use common text features to construct the first classifier. We extract opinion words from consumer reviews, and then we ranked these opinion words according to their importance. We also employ extracted opinion w...

Word co-occurrences form a graph, regarding words as nodes and co-occurrence relations as branches. Thus, a co-occurrence graph can be constructed by co-occurrence relations in a corpus. This paper discusses a clustering method of the co-occurrence graph, the decomposition of the graph, from a graph-theoretical viewpoint. Since one of the applications for the clustering results is the ambiguity...

In this paper, we describe an accurate and effective event detection method to detect events from Twitter stream. It detects events using visual information as well as textual information to improve the performance of the mining. It monitors Twitter stream to pick up tweets having texts and photos and stores them into database. Then it applies mining algorithm to detect the event. Firstly, it d...

According to psychological learning theory an important principle governing language acquisition is co-occurrence. For example, when we perceive language, our brain seems to unconsciously analyze and store the co-occurrence patterns of the words. And during language production, these co-occurrence patterns are reproduced. The applicability of this principle is particularly obvious in the case o...

This research examines the determinants of living arrangements among the Chinese elderly by distinguishing the seniors by sex, residence and age. Through analyzing data from the 2011 wave of Chinese Longitudinal Healthy Longevity Survey (CLHLS), the results show that about 80% of the elderly still chose to co-reside with other family members and only 2% of them lived in institutions. Having chi...

A set of standard answers facilitates answering emails at customer care centers. Matching the text of user emails to the standard answers may not be productive because they do not necessarily have the same wording. Therefore we examine archived email-answer pairs and establish query-answer term co-occurrences. When a new user email arrives, we replace query words with most co-occurring answer w...