Query-sensitive mutual reinforcement chain and its application in query-oriented multi-document summarization

Improving the Estimation of Word Importance for News Multi-Document Summarization

“…A handful of investigations have productively explored the mutually reinforcing relationship between word and sentence importance, iteratively re-estimating each in either supervised or unsupervised framework (Zha, 2002;Wan et al, 2007;Wei et al, 2008;Liu et al, 2011). Most existing work directly focuses on predicting sentence importance, with emphasis on the formalization of the problem (Kupiec et al, 1995;Celikyilmaz and Hakkani-Tur, 2010;Litvak et al, 2010).…”

“…KL: Prior work has shown that having estimates of sentence importance can also help in estimating word importance (Wan et al, 2007;Liu et al, 2011;Wei et al, 2008). The summarizer based on KL-divergence assigns importance to sentences directly, in a complex function according to the word distribution in the sentence.…”

Generating event storylines from microblogs

“…Another type is based on matrix decomposition [17,35,31]. Some prior researches focus on clustering query-induced results [37].…”

“…Query-sensitive Mutual Reinforcement Chain (Qs-MRC) [37]: extends the mutual reinforcement principle between sentence and term to document-sentence-term mutual reinforcement chain, and uses query-sensitive similarity to measure the affinity between the pair of texts;…”

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

“…Many methods for generic summarization can be extended to incorporate the query information [SBC03,WLLH08].…”