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Most documents are about more than one subject, but many NLP and IR techniques implicitly assume documents have just one topic. We describe new clues that mark shifts to new …...

This paper considers several important issues for monolingual and multilingual link detection. The experimental results show that nouns, verbs, adjectives and compound nouns are useful to represent news stories; story …...

We present a domain-independent topic segmentation algorithm for multi-party speech. Our feature-based algorithm com- bines knowledge about content using a text-based algorithm as a feature and about form using linguistic …...

Topic segmentation, which aims to fmd the boundaries between topic blocks in a text, is an important task for semantic analysis of texts. Although different solutions have been proposed for …...

Topic segmentation and identification are of- ten tackled as separate problems whereas they are both part of topic analysis. In this article, we study how topic identification can help to …...

We present a domain-independent unsuper- vised topic segmentation approach based on hybrid document indexing. Lexical chains have been successfully employed to evalu- ate lexical cohesion of text segments and to …...

Topic segmentation was addressed by a large amount of work from which it is not easy to draw conclusions, especially about the need for knowl- edge. In this article, we …...

A probabilistic segment model combining lexical cohesion and disruption for topic seg- mentation Identifying topical structure in any text-like data is a challenging task. Most existing techniques rely either on …...

Topic segmentation classically relies on one of two criteria, either finding areas with co- herent vocabulary use or detecting discontinu- ities. In this paper, we propose a segmenta- tion criterion …...

Online forum discussions proceed differ- ently from face-to-face conversations and any single thread on an online forum con- tains posts on different subtopics. This work aims to characterize the content …...

Topic segmentation traditionally relies on lexical cohesion measured through word re-occurrences to output a dense segmen- tation, either linear or hierarchical. In this paper, a novel organization of the topical …...

AbstractTopic segmentation plays an important role for discourse parsing and information retrieval. Due to the absence of training data, previous work mainly adopts unsupervised methods to rank semantic coherence between …...

In this article, we describe FrNewsLink, a corpus allowing to address several applicative tasks that we make publicly available. It gathers several resources from TV Broadcast News (TVBN) shows and …...

AbstractTopic segmentation is critical in key NLP tasks and recent works favor highly effective neural supervised approaches. However, current neural solutions are arguably limited in how they model context. In …...

AbstractText segmentation is a natural language processing task with popular applications, such as topic segmentation, element discourse extraction, and sentence tokenization. Much work has been done to develop accurate segmentation …...

AbstractThe multi-head self-attention mechanism of the transformer model has been thoroughly investigated recently. In one vein of study, researchers are interested in understanding why and how transformers work. In another …...

AbstractVideo-grounded dialogue understanding is a challenging problem that requires machine to perceive, parse and reason over situated semantics extracted from weakly aligned video and dialogues. Most existing benchmarks treat both …...