Research on keyword extraction based on abstract extraction

Keyword Extraction Based on Implicit Feedback

To improve the results from search engines and make them more personalized for the user, we need to find out about the interests of a particular user. Many of the search personalization methods analyse documents visited by the user and from these documents infer the user’s interests. However, this approach is not accurate, because the user is rarely interested in the whole document; he might be...

Automatic Keyword Extraction on Twitter

In this paper, we build a corpus of tweets from Twitter annotated with keywords using crowdsourcing methods. We identify key differences between this domain and the work performed on other domains, such as news, which makes existing approaches for automatic keyword extraction not generalize well on Twitter datasets. These datasets include the small amount of content in each tweet, the frequent ...

Abstract Generation Based On Rhetorical Structure Extraction

generation is, like Machine Translation, one of the ultimate goal of Natural Language Processing. However, since conventional word–frequency– based abstract generation systems(e.g. [Kuhn 58]) are lacking in inter-sentential or discourse-structural analysis, they are liable to generate incoherent abstracts. On the other hand, conventional knowledge or script–based abstract generation systems(e.g...

Cluster-based Keyword Extraction Approach

Keyword extraction for blogs based on content richness

In this paper, a method is proposed to extract topic keywords of blogs, based on the richness of content. If a blog includes rich content related to a topic word, the word can be considered as a keyword of the blog. For this purpose, a new measure, richness, is proposed, which indicates how much a blog covers the trendy subtopics of a keyword. In order to obtain trendy subtopics of keywords, we...