Automatic identification of subtopics for a given topic is desirable because it eliminates the need for manual construction of domain-specific topic hierarchies. In this paper, we design features based on corpus statistics to design a classifier for identifying the (subtopic, topic) links between phrase pairs. We combine these features along with the commonly-used syntactic patterns to classify...

Existing topic tracking methods are mostly for news and forum data, which lack of statistical methods for microblogging on relevant topics. Combined with characteristics of micro-blog information, the paper proposes a microblogging statistical methods based on semantic similarity. Firstly by building topic semantic model and then use the HowNet semantic similarity calculation of two terms, and ...

Topic models can learn topics that are highly interpretable, semantically-coherent and can be used similarly to subject headings. But sometimes learned topics are lists of words that do not convey much useful information. We propose models that score the usefulness of topics, including a model that computes a score based on pointwise mutual information (PMI) of pairs of words in a topic. Our PM...

A new statistical method for Language Modeling and spoken document classification is proposed. It is based on a mixture of topic dependent probabilities. Each topic dependent probability is in turn a mixture of n-gram probabilities and the probability of Kullback-Lieber (KL) distances between key-word unigrams and distribution obtained from the content of a cache memory. Experimental result on ...

To solve the problems in traditional automatic Chinese summarization, a new method based on the word concept and clustering is presented in this paper. Different from the normal statistical method, concept is used as feature instead of word. Also, instead of word frequency statistics, word concept frequency statistics (WCFS) is used in our approach. For each paragraph, a conceptual vector space...

72 1024x768 normal 0 false false false en-us x-none ar-sa background : by providing a picture from published articles in a field, bibliometric studies can inform policy-makers in their challenging research funding decisions. in this regard, we applied bibliometric analysis to the iranian pediatrics articles published in pubmed indexed journals between 1975 and 2007. methods : we evaluated all p...

We propose a method for supporting query refinement using topical term clusters. First, we propose a new term weighting method that can extract terms strongly related to a specific topic, because a document set retrieved with an ambiguous query may include divergent topics. Our formulation of term weighting is based on the statistics of term co-occurrence. Then, we generate term clusters using ...