[PDF] Top 20 A Hybrid Hierarchical Model for Multi Document Summarization

... ing multi-document summarization to produce co- herent and semantically relevant ...on summarization depend on a word score function, which is used to measure sentence rank scores based on ... See full document

... as multi-relational data where objects have interactions with others based on different relations, we attempt to map sentence relatedness within multiple topics to heterogeneous relations in this ...addressing ... See full document

... There are a number of directions we plan to pur- sue in the future in order to improve our method. First, we can possibly apply more linguistic knowl- edge to improve the quality of sentence compres- sion. Currently the ... See full document

... text summarization with summaries organized by topic and paragraph based on hierarchical structure topic ...multiple hierarchical structure topic mod- els run over the same corpus under simi- lar ... See full document

... mal expressions. Some previous works explore the effect of comments or social contexts in single document summarization such as blog summariza- tion (Hu et al., 2008; Yang et al., 2011). However, the ... See full document

... extractive summarization, it is important to acquire the relationship between sentences and aspects for sentence ...and document level in the h-uHDP ...one document usually talk about one same ... See full document

... in multi-document summarization task, for ...45 document sets respectively. Each document set has 25 news articles for summarization and 4 human-written summaries as ground ... See full document

... Our method derives an overall informativeness score for each candidate summary, then selects the one with the highest score. This is related to the growing body of research in global optimization, which selects the most ... See full document

... a document and then use another LSTM to predict binary labels for each sentence in the ...Our model also employs a hierarchi- cal document encoder, but we adopt a hierarchical transformer ... See full document

... There are two parameters to tune in our model. The first parameter is a in Equation (11) that controls the tradeoff between influence from topics and from sentences. The second one is the topic number K in LDA ... See full document

... A multi-document extension of RST is Cross-document Structure Theory (CST), which has been applied to MDS (Zhang et ...of summarization based on lightweight ... See full document

... Note that we use u to represent the vector dimen- sion throughout the model description (specific value settings are given in Section 5). The rep- resentations for news sentences S and news docu- ments D are ... See full document

... linear model for the problem of text summarization, where a summary preserves the information cov- erage as much as possible in comparison to the original document ...the Multi- Ling contest ... See full document

... quality model that prefers relevant sentences with a global diversity model encouraging non-overlapping ...quality model can depend on arbitrary features, and its parameters can be effi- ciently ... See full document

... real-time summarization is based on high-redundancy text (Chua and Asur, 2013; Lin et ...neous document collections, there are important facts and arguments that appear only in few of the available docu- ... See full document

... efficient multi-document summarization as the internet provides the access to a very large amount of data in a particular language & it also helps them in making decision in a lesser ... See full document

... Single document summarization (SDS) sys- tems have benefited from advances in neu- ral encoder-decoder model thanks to the avail- ability of large ...However, multi- document ... See full document

... summarization. PBTMSum combining pattern mining techniques with LDA topic modelling could generate discriminative and semantic rich representations for topics and documents so that the most representative and ... See full document

... Hierarchical summarization has two important strengths in the context of large-scale summariza- tion. First, the information presented at the start is small and grows only as the user directs it, so as not ... See full document

... tion model which can effectively process multi- ple input documents and distill abstractive sum- ...Our model augments the previously pro- posed Transformer architecture with the ability to encode ... See full document