Greedy Algorithm

This paper reports a new method for suggesting word associations, based on a greedy algorithm that employs Chi- square statistics on joint frequencies of pairs of word groups compared against …...

This paper presents a new approach to automatic word categorization which im- proves both the efficiency of the algorithm and the quality of the formed clusters. The unigram and the …...

Lexical Chains are powerful representa- tions of documents. In particular, they have successfully been used in the field of Automatic Text Summarization. How- ever, until now, Lexical Chaining algo- rithms …...

We discuss text summarization in terms of maximum coverage problem and its vari- ant. We explore some decoding algorithms including the ones never used in this sum- marization formulation, such …...

Thanks to its simplicity, social tagging system has accumulated huge amount of user contributed tags. However, user contributed tags lack explicit hierarchi- cal structure, while many tag-based ap- plications would …...

We treat the text summarization problem as maximizing a submodular function under a budget constraint. We show, both theoretically and empirically, a modified greedy algorithm can efficiently solve the budgeted …...

The aim of this paper is to perform Word Sense induction (WSI); which clusters web search results and produces a diversified list of search results. It describes the WSI system …...

We propose a new optimization frame- work for summarization by generalizing the submodular framework of (Lin and Bilmes, 2011). In our framework the sum- marization desideratum is expressed as a …...

The anchor words algorithm performs provably efficient topic model inference by finding an approximate convex hull in a high-dimensional word co-occurrence space. However, the existing greedy al- gorithm often selects …...

Automated text summarization is aimed at extracting essential information from orig- inal text and presenting it in a minimal, often predefined, number of words. In this paper, we introduce a …...

Opinion summarization is the task of pro- ducing the summary of a text, such that the summary also preserves the sentiment of the text. Opinion Summarization is thus a trade-off …...

The task of cross-language document summarization is to create a summary in a target language from documents in a dif- ferent source language. Previous meth- ods only involve direct extraction …...

AbstractSubmodular maximization with the greedy algorithm has been studied as an effective approach to extractive summarization. This approach is known to have three advantages: its applicability to many useful submodular …...

AbstractDocument alignment aims to identify pairs of documents in two distinct languages that are of comparable content or translations of each other. Such aligned data can be used for a …...