A new approach on search for similar documents with multiple categories using fuzzy clustering

Saraçoğlu, Rıdvan; Tutuncu, Kemal; Allahverdi, Novruz

doi:10.1016/j.eswa.2007.04.003

Cited by 34 publications

(18 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Other related techniques [25,27,30]view a document as a long query and retrieve other realted documents. Smucker and Allan [26] proposed a search tool FindSimilar by users' similarity browsing.…”

Section: Related Workmentioning

confidence: 99%

Generating queries from user-selected text

Lee

Croft

2012

Proceedings of the 4th Information Interaction in Context Symposium

View full text Add to dashboard Cite

People browsing the web or reading a document may see text passages that describe a topic of interest, and want to know more about it by searching. Manually formulating a query from that text can be difficult, however, and an effective search is not guaranteed. In this paper, to address this scenario, we propose a learning-based approach which generates effective queries from the content of an arbitrary userselected text passage. Specifically, the approach extracts and selects representative chunks (noun phrases or named entities) from the content (a text passage) using a rich set of features. We carry out experiments showing that the selected chunks can be effectively used to generate queries both in a TREC environment, where weights and query structure can be directly incorporated, and with a "black-box" web search engine, where query structure is more limited.

show abstract

Section: Related Workmentioning

confidence: 99%

Generating queries from user-selected text

Lee

Croft

2012

Proceedings of the 4th Information Interaction in Context Symposium

View full text Add to dashboard Cite

show abstract

“…There are other text classification techniques that have explored in other applications such as in [19][20] [21].…”

Section: Related Workmentioning

confidence: 99%

A Novel Rhetorical Structure Approach for Classifying Arabic Security Documents

Mathkour¹

2009

IJCTE

View full text Add to dashboard Cite

Abstract-Security Documents classification is aimed at securing documents from being illegally disclosed. Classifying a portion of a document as a 'secret' depends on the type of effect its disclosure will have in an organization. In this respect, Information is classified according to their critical semantic (i.e. its context or value and intended uses or audience at particular time or situation). Understanding the semantic of a document is not an easy task. The rhetorical structure theory (RST) is one of the leading theories that have been applied successfully in text processing and understanding. In this paper, we will describe a novel approach to automatically classify Arabic Security documents using RST.

show abstract

“…In turn, in [14] a formal ontology is presented which not only allows for representing the structure of multimedia documents but also to connect with arbitrary background knowledge on the web. This paper presents a fuzzy-based approach to the above mentioned problem different from other authors' [2,9]. In particular, the paper [2] presents a method based on the term frequency-inverse document frequency to auto-extract the keywords in the patent literature.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, the paper [2] presents a method based on the term frequency-inverse document frequency to auto-extract the keywords in the patent literature. In [9] the case is investigated which includes the documents that belong to more than one category and a similar document search system that uses fuzzy clustering is illustrated. The method illustrated in this paper presents two relevant features: the use of the natural language to characterize a document through qualitative information (in order to help the authors in developing metadata) and the definition of a matching, during a search session, between the user profile and the document he/she is looking for.…”

Section: Introductionmentioning

confidence: 99%

Searching Web Documents Using a Fuzzy-Based Method

Fischetti

Nappi²

2017

AJFAM

View full text Add to dashboard Cite

Web searching could be more fruitful if a user could easily find documents which satisfy his/her needs in terms of structure, format and contents. Herein a solution through a fuzzy linguistic description of the document is proposed, a linguistic variant of standard metadata types. Linguistic expressions are used to qualitatively represent both meta-information and user needs and a matching system is developed to select the most compatible documents with the user profile. The documents retrieved by a web search engine are organized in clusters and ordered in each cluster.

show abstract

A new approach on search for similar documents with multiple categories using fuzzy clustering

Cited by 34 publications

References 23 publications

Generating queries from user-selected text

Generating queries from user-selected text

A Novel Rhetorical Structure Approach for Classifying Arabic Security Documents

Searching Web Documents Using a Fuzzy-Based Method

Contact Info

Product

Resources

About