In the context of unified messaging, a textual message may have to be reduced in length for display on certain mobile devices. This paper presents a new method to extract sentences that deal with a certain topic from a given text. The approach is based on automatically computed lists of words that represent the desired topics. These word lists also give semantic hints on how to shorten sentences, extending previous methods that rely on syntactical clues only. The method has been evaluated for extraction accuracy and by human subjects for informativeness of the resulting extracts. 1
This paper describes ongoing work on how to automatically identify and use key phrases extracted fr...
Topic segmentation plays an important role for discourse analysis and document understanding.Previou...
Topic segmentation classically relies on one of two criteria, either finding areas with co-herent vo...
To understand text, we must relate it with specified situations. This paper, on the basis of such an...
Massive amount of short texts such as tweets, reviews, and social media posts are available on the i...
. We investigate the problem of text segmentation by topic. Applications for this task include topic...
Much currently transmitted information takes the form of e-mails or SMS text messages and so extract...
Short texts are a common source of knowledge, and the extraction of such valuable information is ben...
User generated content in the form of customer reviews, blogs or tweets is an emerging and rich sour...
Recently, there has been an exponential rise in the use of online social media systems like Twitter ...
Social media, such as tweets on Twitter and Short Message Service (SMS) messages on cellular network...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Most documents are about more than one subject, but the majority of natural language processing algo...
© 2018 IEEE. To address the data sparsity problem in short text understanding, various alternative t...
Small and varying screen sizes of mobile devices pose a big problem for digital Teletext service to ...
This paper describes ongoing work on how to automatically identify and use key phrases extracted fr...
Topic segmentation plays an important role for discourse analysis and document understanding.Previou...
Topic segmentation classically relies on one of two criteria, either finding areas with co-herent vo...
To understand text, we must relate it with specified situations. This paper, on the basis of such an...
Massive amount of short texts such as tweets, reviews, and social media posts are available on the i...
. We investigate the problem of text segmentation by topic. Applications for this task include topic...
Much currently transmitted information takes the form of e-mails or SMS text messages and so extract...
Short texts are a common source of knowledge, and the extraction of such valuable information is ben...
User generated content in the form of customer reviews, blogs or tweets is an emerging and rich sour...
Recently, there has been an exponential rise in the use of online social media systems like Twitter ...
Social media, such as tweets on Twitter and Short Message Service (SMS) messages on cellular network...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Most documents are about more than one subject, but the majority of natural language processing algo...
© 2018 IEEE. To address the data sparsity problem in short text understanding, various alternative t...
Small and varying screen sizes of mobile devices pose a big problem for digital Teletext service to ...
This paper describes ongoing work on how to automatically identify and use key phrases extracted fr...
Topic segmentation plays an important role for discourse analysis and document understanding.Previou...
Topic segmentation classically relies on one of two criteria, either finding areas with co-herent vo...