Add to ORKGIn order to solve problems of reliability of systems based on lexical repetition and problems of adaptability of language-dependent systems, we present a context-based topic segmentation system based on a new informative similarity measure based on word co-occurrence. In particular, our evaluation with the state-of-the-art in the domain i.e. the c99 and the TextTiling algorithms shows improved results both with and without the identification of multiword units
Dividing documents into topically-coherent units and discovering their topic might have many uses. W...
AbstractTopic segmentation is important for many natural language processing applications such as in...
International audienceThematic analysis is essential for many Natural Language Processing (NLP) appl...
In order to solve problems of reliability of systems based on lexical repetition and problems of ada...
Most documents are about more than one subject, but the majority of natural language processing algo...
. We investigate the problem of text segmentation by topic. Applications for this task include topic...
Topic segmentation classically relies on one of two criteria, either finding areas with co-herent vo...
Most documents are aboutmore than one subject, but the majority of natural language processing algor...
Topic segmentation is essential for a lot of Natural Language Processing (NLP) applications, such as...
International audienceSeveral evaluation metrics have been proposed for topic seg-mentation. Most of...
We present a new composite similarity metric that combines information from multiple linguistic indi...
The recent explosion of available audio-visual media is the new challenge for information retrieval ...
This paper deals with the problem of automatic topic detection in text documents. The proposed metho...
Abstract: Mining is a process of knowledge extraction with some meaningful information. Topic Mining...
In this paper, we attack the problem of forming extracts for text summarization. Forming extracts in...
Dividing documents into topically-coherent units and discovering their topic might have many uses. W...
AbstractTopic segmentation is important for many natural language processing applications such as in...
International audienceThematic analysis is essential for many Natural Language Processing (NLP) appl...
In order to solve problems of reliability of systems based on lexical repetition and problems of ada...
Most documents are about more than one subject, but the majority of natural language processing algo...
. We investigate the problem of text segmentation by topic. Applications for this task include topic...
Topic segmentation classically relies on one of two criteria, either finding areas with co-herent vo...
Most documents are aboutmore than one subject, but the majority of natural language processing algor...
Topic segmentation is essential for a lot of Natural Language Processing (NLP) applications, such as...
International audienceSeveral evaluation metrics have been proposed for topic seg-mentation. Most of...
We present a new composite similarity metric that combines information from multiple linguistic indi...
The recent explosion of available audio-visual media is the new challenge for information retrieval ...
This paper deals with the problem of automatic topic detection in text documents. The proposed metho...
Abstract: Mining is a process of knowledge extraction with some meaningful information. Topic Mining...
In this paper, we attack the problem of forming extracts for text summarization. Forming extracts in...
Dividing documents into topically-coherent units and discovering their topic might have many uses. W...
AbstractTopic segmentation is important for many natural language processing applications such as in...
International audienceThematic analysis is essential for many Natural Language Processing (NLP) appl...