Keyword and Keyphrase Extraction Techniques: A Literature Review

Abstract

In this paper we present a survey of various techniques available in text mining for keyword and keyphrase extraction. Keywords and keyphrases are very useful in analyzing large amount of textual material quickly and efficiently search over the internet besides being useful for many other purposes. Keywords and keyphrases are set of representative words of a document that give high-level specification of the content for interested readers. They are used highly in the field of Computer Science especially in Information Retrieval and Natural Language Processing and can be used for index generation, query refinement, text summarization, author assistance, etc. We have also discussed some important feature selection metrics generally employed by researchers to rank candidate keywords and keyphrases according to their importance.

Keyphrase Generation: A Multi-Aspect Survey

“…Unlike similar recent reviews such as [19], [20], or [21] that focus entirely on extractive KG (or KE), the main interest of this work in the more recent and technically advanced AKG studies which are examined in details. Particular attention is paid to the network structures and the enhancement mechanisms, as well as to the evaluation process the authors follow.…”

Scheduling aspects in keyword extraction problem

“…The large amount of textual information, mostly unstructured and without any semantic description, available on the Internet requires the development of tools that help end users to efficiently process such amount of data and quickly search, classify, and assess natural language documents according to the end users' needs. The keyword extraction is a main underlying task of many NLP tools as it is often an important step of many text mining applications, for instance, relevance assessment, index generation, query refinement, document categorization, named-entity recognition, document similarity measurements, text summarization, and so on (Beliga, 2014;Siddiqi and Sharan, 2015). Therefore, in this paper we have selected the keyword extraction problem due to its complexity and also as a good example from a wide range of NLP applications or their relevant parts.…”

Keyword extraction from single documents using mean word intermediate distance

“…Major works in the field of keyword extraction using different approaches as outlined in the previous section have been reported by Siddiqi et al [2]. Some of the other related works are as follows:…”