Keyphrase extraction is a textual information processing task concerned with the automatic
extraction of representative and characteristic phrases from a document that express all the …

As the amount of generated information grows, reading and summarizing texts of large
collections turns into a challenging task. Many documents do not come with descriptive …

We propose an unsupervised keyphrase extraction model that encodes topical information
within a multipartite graph structure. Our model represents keyphrase candidates and topics …

An essential part of a text generation task is to extract critical information from the text.
People usually obtain critical information in the text via manual extraction; however, the …

Keyphrase prediction aims to generate phrases (keyphrases) that highly summarizes a
given document. Recently, researchers have conducted in-depth studies on this task from …

Automatic keyphrase extraction techniques aim to extract quality keyphrases for higher level
summarization of a document. Majority of the existing techniques are mainly domain …

With growing amounts of available textual data, development of algorithms capable of
automatic analysis, categorization, and summarization of these data has become a …

The goal of keyword extraction is to extract from a text, words, or phrases indicative of what it
is talking about. In this work, we look at keyword extraction from a number of different …

Keyword provide a brief profile of document contents and serve as an important method for
quickly obtaining the document's themes. Traditional keyword extraction methods are mostly …

Topical PageRank (TPR) uses latent topic distribution inferred by Latent Dirichlet Allocation
(LDA) to perform ranking of noun phrases extracted from documents. The ranking procedure …