While automatic keyphrase extraction has been examined extensively, state-of-theart
performance on this task is still much lower than that on many core natural language …

Due to the considerable growth of the volume of text documents on the Internet and in digital
libraries, manual analysis of these documents is no longer feasible. Having efficient …

Keyphrase provides highly-condensed information that can be effectively used for
understanding, organizing and retrieving text content. Though previous studies have …

The large and growing amounts of online scholarly data present both challenges and
opportunities to enhance knowledge discovery. One such challenge is to automatically …

In this paper, we address the keyphrase extraction problem as sequence labeling and
propose a model that jointly exploits the complementary strengths of Conditional Random …

This paper describes the organization and results of the automatic keyphrase extraction task
held at the Workshop on Semantic Evaluation 2010 (SemEval-2010). The keyphrase …

We present a content-based method for recommending citations in an academic paper draft.
We embed a given query document into a vector space, then use its nearest neighbors as …

In our study, we examine the impact of citation network structures on the ability to discern
valuable research topics in Computer Science literature. We use the bibliographic …

Due to the exponential growth of textual data and web sources, an automatic mechanism is
required to identify relevant information embedded within them. The utility of Automatic …

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