What are the key structures existing in a large real-world MMORPG (Massively Multiplayer Online Role-Playing Game) graph? How can we compactly summarize an graph with hierarchical node labels, considering substructures at different levels of hierarchy? Recent MMORPGs generate complex interactions between entities inducing heterogeneous where each entity has labels. Succinctly summarizing is cru...

University of Ljubljana Faculty of Computer and Information Science Ercan Canhasi Graph-based models for multi-document summarization is thesis is about automatic document summarization, with experimental results on general, query, update and comparative multi-document summarization (MDS). We describe prior work and our own improvements on some important aspects of a summarization system, incl...

With the noteworthy expansion of textual data sources in recent years, easy, quick, and precise text processing has become a challenge for key qualifiers. Automatic summarization is process squeezing documents into shorter summaries to facilitate verification their basic contents, which must be completed without losing vital information features. The most difficult retrieval task summarization,...

Previous work for text summarization in scientific domain mainly focused on the content of input document, but seldom considering its citation network. However, papers are full uncommon domain-specific terms, making it almost impossible model to understand true meaning without help relevant research community. In this paper, we redefine task by utilizing their graph and propose a graph-based CG...

Recent years have shown that graphs are an adequate text representation model for summarization. For this years’ TAC update summarization challenge, we extended our graph-based summarization system with coreference relations and sentence compression. Our results show that using coreference relations did not result in a significant performance gain; sentence compression had a negative effect on ...

Neural network-based encoder–decoder (ED) models are widely used for abstractive text summarization. While the encoder first reads source document and embeds salient information, decoder starts from such encoding to generate summary word-by-word. However, drawback of ED model is that it treats words sentences equally, without discerning most relevant ones others. Many researchers have investiga...

Sentence Connectivity is a textual characteristic that may be incorporated intelligently for the selection of sentences of a well meaning summary. However, the existing summarization methods do not utilize its potential fully. The present paper introduces a novel method for singledocument text summarization. It poses the text summarization task as an optimization problem, and attempts to solve ...