The various meanings of discourse connectives like while and however are difficult to identify and annotate, even for trained human annotators. This problem is all the more important since connectives are salient textual markers of cohesion and need to be correctly interpreted for many Natural Language Processing applications. In this paper, we suggest an alternative route to reach a reliable a...

This paper describes a novel Bayesian approach to unsupervised topic segmentation. Unsupervised systems for this task are driven by lexical cohesion: the tendency of wellformed segments to induce a compact and consistent lexical distribution. We show that lexical cohesion can be placed in a Bayesian context by modeling the words in each topic segment as draws from a multinomial language model a...

This paper presents an algorithm for text summarization using the thematic hierarchy of a text. The algorithm is intended to generate a onepage summary for the user, thereby enabling the user to skim large volumes of an electronic book on a computer display. The algorithm rst detects the thematic hierarchy of a source text with lexical cohesion measured by term repetitions. Then, it identi es b...

Discourse cohesion facilitates text comprehension and helps the reader form a coherent narrative. In this study, we aim to computationally analyze discourse in scientific scholarly texts using multilayer network representation quantify writing quality of document. Exploiting hierarchical structure texts, design section-level document-level metrics assess extent lexical text. We use publicly ava...

K-means algorithm is a relatively simple and fast gather clustering algorithm. However, the initial clustering center of the traditional k-means algorithm was generated randomly from the dataset, and the clustering result was unstable. In this paper, we propose a novel method to optimize the selection of initial centroids for k-means algorithm based on the small world network. This paper firstl...

This paper describes a quantitative indicator for segmenting narrative text into coherent scenes. The indicator, called the lexical cohesion pro le (LCP), records lexical cohesiveness of words in a xed-length window moving word by word on the text. The cohesiveness of words, which represents their coherence, is computed by spreading activation on a semantic network. The basic idea of LCP is: (1...