2014/05/17 by Ercan Canhasi, Canhasi, Ercan
Computer Science · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Topic Modeling #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.1405.7975
openalex publication_date 2014/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Multi-document summarization is a process of automatic generation of a compressed version of the given collection of documents. Recently, the graph-based models and ranking algorithms have been actively investigated by the extractive document summarization community. While most work to date focuses on homogeneous connecteness of sentences and heterogeneous connecteness of documents and sentences (e.g. sentence similarity weighted by document importance), in this paper we present a novel 3-layered graph model that emphasizes not only sentence and document level relations but also the influence of under sentence level relations (e.g. a part of sentence similarity).