Profile-based event tracking

Baoli Li; Wenjie Li; Qin Lu; Mingli Wu

doi:10.1145/1076034.1076163

Profile-based event tracking

Baoli Li, Wenjie Li, Qin Lu, Mingli Wu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

12 Citations (Scopus)

Abstract

In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.

Original language	English
Title of host publication	SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages	631-632
Number of pages	2
DOIs	https://doi.org/10.1145/1076034.1076163
Publication status	Published - 1 Dec 2005
Event	28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 - Salvador, Brazil Duration: 15 Aug 2005 → 19 Aug 2005

Conference

Conference	28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005
Country/Territory	Brazil
City	Salvador
Period	15/08/05 → 19/08/05

Keywords

event tracking
topic detection and tracking
topic tracking

ASJC Scopus subject areas

Information Systems

More information

10.1145/1076034.1076163

Cite this

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title = "Profile-based event tracking",

abstract = "In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.",

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Li, B, Li, W, Lu, Q & Wu, M 2005, Profile-based event tracking. in SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. pp. 631-632, 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005, Salvador, Brazil, 15/08/05. https://doi.org/10.1145/1076034.1076163

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AU - Li, Baoli

AU - Li, Wenjie

AU - Lu, Qin

AU - Wu, Mingli

PY - 2005/12/1

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N2 - In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.

AB - In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.

KW - event tracking

KW - topic detection and tracking

KW - topic tracking

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U2 - 10.1145/1076034.1076163

DO - 10.1145/1076034.1076163

M3 - Conference article published in proceeding or book

SN - 1595930345

SN - 9781595930347

SP - 631

EP - 632

BT - SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

T2 - 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005

Y2 - 15 August 2005 through 19 August 2005

ER -

Profile-based event tracking

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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