Multi-topic information filtering with a single user profile

Nikolaos Nanas; Victoria Uren; Anne de Roeck; John Domingue

doi:10.1007/978-3-540-24674-9_42

Multi-topic information filtering with a single user profile

Nikolaos Nanas, Victoria Uren, Anne de Roeck, John Domingue

Operations & Information Management

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

Original language	English
Title of host publication	Methods and applications of artificial intelligence
Subtitle of host publication	third Hellenic conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings
Editors	George A. Vouros, Themistoklis Panayiotopoulos
Place of Publication	Berlin (DE)
Publisher	Springer
Pages	400-409
Number of pages	10
ISBN (Electronic)	978-3-540-24674-9
ISBN (Print)	978-3-540-21937-8
DOIs	https://doi.org/10.1007/978-3-540-24674-9_42
Publication status	Published - 2004
Event	3rd Hellenic Conference on Artificial Intelligence - Samos, Greece Duration: 5 May 2004 → 8 May 2004

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Volume	3025
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd Hellenic Conference on Artificial Intelligence
Abbreviated title	SETN 2004
Country/Territory	Greece
City	Samos
Period	5/05/04 → 8/05/04

Access to Document

10.1007/978-3-540-24674-9_42

Cite this

Nanas, N., Uren, V., de Roeck, A., & Domingue, J. (2004). Multi-topic information filtering with a single user profile. In G. A. Vouros, & T. Panayiotopoulos (Eds.), Methods and applications of artificial intelligence: third Hellenic conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings (pp. 400-409). (Lecture notes in computer science; Vol. 3025). Springer. https://doi.org/10.1007/978-3-540-24674-9_42

Nanas, Nikolaos ; Uren, Victoria ; de Roeck, Anne et al. / Multi-topic information filtering with a single user profile. Methods and applications of artificial intelligence: third Hellenic conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings. editor / George A. Vouros ; Themistoklis Panayiotopoulos. Berlin (DE) : Springer, 2004. pp. 400-409 (Lecture notes in computer science).

@inproceedings{e06e103696aa4ae79ff27b6fb457e387,

title = "Multi-topic information filtering with a single user profile",

abstract = "In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.",

author = "Nikolaos Nanas and Victoria Uren and {de Roeck}, Anne and John Domingue",

year = "2004",

doi = "10.1007/978-3-540-24674-9_42",

language = "English",

isbn = "978-3-540-21937-8",

series = "Lecture notes in computer science",

publisher = "Springer",

pages = "400--409",

editor = "Vouros, {George A.} and Themistoklis Panayiotopoulos",

booktitle = "Methods and applications of artificial intelligence",

address = "Germany",

note = "3rd Hellenic Conference on Artificial Intelligence, SETN 2004 ; Conference date: 05-05-2004 Through 08-05-2004",

}

Nanas, N, Uren, V, de Roeck, A & Domingue, J 2004, Multi-topic information filtering with a single user profile. in GA Vouros & T Panayiotopoulos (eds), Methods and applications of artificial intelligence: third Hellenic conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings. Lecture notes in computer science, vol. 3025, Springer, Berlin (DE), pp. 400-409, 3rd Hellenic Conference on Artificial Intelligence, Samos, Greece, 5/05/04. https://doi.org/10.1007/978-3-540-24674-9_42

Multi-topic information filtering with a single user profile. / Nanas, Nikolaos; Uren, Victoria; de Roeck, Anne et al.
Methods and applications of artificial intelligence: third Hellenic conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings. ed. / George A. Vouros; Themistoklis Panayiotopoulos. Berlin (DE): Springer, 2004. p. 400-409 (Lecture notes in computer science; Vol. 3025).

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - Multi-topic information filtering with a single user profile

AU - Nanas, Nikolaos

AU - Uren, Victoria

AU - de Roeck, Anne

AU - Domingue, John

PY - 2004

Y1 - 2004

N2 - In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

AB - In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

UR - http://link.springer.com/chapter/10.1007%2F978-3-540-24674-9_42

U2 - 10.1007/978-3-540-24674-9_42

DO - 10.1007/978-3-540-24674-9_42

M3 - Conference publication

SN - 978-3-540-21937-8

T3 - Lecture notes in computer science

SP - 400

EP - 409

BT - Methods and applications of artificial intelligence

A2 - Vouros, George A.

A2 - Panayiotopoulos, Themistoklis

PB - Springer

CY - Berlin (DE)

T2 - 3rd Hellenic Conference on Artificial Intelligence

Y2 - 5 May 2004 through 8 May 2004

ER -

Nanas N, Uren V, de Roeck A, Domingue J. Multi-topic information filtering with a single user profile. In Vouros GA, Panayiotopoulos T, editors, Methods and applications of artificial intelligence: third Hellenic conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings. Berlin (DE): Springer. 2004. p. 400-409. (Lecture notes in computer science). doi: 10.1007/978-3-540-24674-9_42

Multi-topic information filtering with a single user profile

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Multi-topic information filtering with a single user profile

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Activities

Supervising Doctoral Students

Cite this