This paper presents a model for keyword extraction, extending the basic concepts commonly used in this task, in order to get a formal background that allows determining the importance of the keywords to the documents. The proposed model combines an artificial immune system with a mathematical background based on information theory; this new model has the advantage that does not need any domain ...

The manner in which keywords fulfill the role of being central to a document is frustratingly still an open question. In this paper, we hope to shed some light on the essence of keywords in scientific articles and thereby motivate the graph-based approach to keyword extraction. We identify the document model captured by the text graph generated as input to a number of centrality metrics, and ov...

We introduce a method that extracts keywords in a language with the help of the other. The method involves estimating preferences for topical keywords and fusing language-specific word statistics. At run-time, we transform parallel articles into word graphs, build crosslingual edges for word statistics integration, and exploit PageRank with word keyness information for keyword extraction. We ap...

This paper presents experiments on how the performance of automatic keyword extraction can be improved, as measured by keywords previously assigned by professional indexers. The keyword extraction algorithm consists of three prediction models that are combined to decide what words or sequences of words in the documents are suitable as keywords. The models, in turn, are built using different def...

Keywords can be considered as condensed versions of documents and short forms of their summaries. In this paper, the problem of automatic extraction of keywords from documents is treated as a supervised learning task. A lexical chain holds a set of semantically related words of a text and it can be said that a lexical chain represents the semantic content of a portion of the text. Although lexi...

As one emerging metadata standard for the Semantic Web, FOAF defines an RDF vocabulary for expressing metadata about people and the relation among them. This paper proposes a novel keyword extraction method to extract FOAF metadata from the Web. The proposed method is based on co-occurrence information of words. Our method extracts relevant keywords depending on the context of a person. Our exp...

---a set of documents that ---through various search and entity extraction methodologies including keywords, phrase extraction, and concept searches. Relevant documents were mined for additional terms that could be used to enhance the efficacy of the search. The team then used additional analytics within the Axcelerate System to examine different documents that contained responsive keywords for...