Polysemy Needs Attention: Short-Text Topic Discovery With Global and Multi-Sense Information

Topic Modeling and Classification of Cyberspace Papers Using Text Mining

The global cyberspace networks provide individuals with platforms to can interact, exchange ideas, share information, provide social support, conduct business, create artistic media, play games, engage in political discussions, and many more. The term cyberspace has become a conventional means to describe anything associated with the Internet and the diverse Internet culture. In fact, cyberspac...

Information Discovery based on Multi-granularity Text Fusion

In this paper we introduce a new information discovery algorithm Multi-granularity Text Fusion (MGTF) on the Web. Granularity means the length of News relevant web documents, such as News web pages, Blog and Micro Blogs, which comes from web uses. The longer the text is, the higher of the granularity it has. Given a topic query on the Internet and the results of different granularity and time-s...

Semi-Productive Polysemy and Sense Extension

Semi-productive Polysemy and Sense Extension

In this paper we discuss various aspects of systematic or conventional polysemy and their formal treatment within an implemented constraint based approach to linguistic representation. We distinguish between two classes of systematic polysemy: constructional polysemy, where a single sense assigned to a lexical entry is contextually specialised, and sense extension, which predictably relates two...

Topic Identification and Discovery on Text and Speech

We compare the multinomial i-vector framework from the speech community with LDA, SAGE, and LSA as feature learners for topic ID on multinomial speech and text data. We also compare the learned representations in their ability to discover topics, quantified by distributional similarity to gold-standard topics and by human interpretability. We find that topic ID and topic discovery are competing...