Topic extraction from news archive using TF*PDF algorithm
Published 26 June 2003
Khoo Khyou Bun, Mitsuru Ishizuka
Citations123
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This work proposes an information system that will extract main topics in a news archive on a weekly basis and by obtaining a weekly report, a user can know what the main news events were in the past week.
Abstract
Busy and no time to digest the news archive....? Ever since the Web wide-spreading, the amount of electronically available information online, especially news archive proliferates and threatens to overwhelm human attention. Seeing this, we propose an information system that will extract the main topics in the news archive in a weekly basis. By getting a weekly report, user can know what were the main news events in the past week. 1.
Keywords
Computer Science
Morgan Kaufmann Publishers Inc. eBooksReadings in information retrieval
1,064 Citations1997Karen Spärck Jones, Peter Willett
A study of retrospective and on-line event detection
731 Citations1998Yiming Yang, Tom Pierce +1 more
This paper applied hierarchical and non-hierarchical document clustering algorithms to a corpus of 15,836 stories, focusing on the exploitation of both content and temporal information, and found the resulting cluster hierarchies highly informative for retrospective detection of previously unidentified events.
Machine LearningStatistical Models for Text Segmentation
687 Citations1999Doug Beeferman, Adam Berger +1 more
Assessment of the approach on quantitative and qualitative grounds demonstrates its effectiveness in two very different domains, Wall Street Journal news articles and television broadcast news story transcripts, using a new probabilistically motivated error metric.
ACM SIGIR ForumOn-Line New Event Detection and Tracking
653 Citations2017James Allan, Ron Papka +1 more
On-line new event detection and tracking
524 Citations1998James Allan, Ron Papka +1 more
The approach to detection uses a single pass clustering algo-rithm and a novel thresholding model that incorporates the properties of events as a major component and the value of \surprising" features that have unusual occurrence characteristics are discussed.
IEEE Intelligent Systems and their ApplicationsLearning approaches for detecting and tracking news events
338 Citations1999Yi Yang, Jaime Carbonell +4 more
The authors extend existing supervised-learning and unsupervised-clustering algorithms to allow document classification based on the information content and temporal aspects of news events to be classified using manually segmented documents.
Classifying news stories using memory based reasoning
261 Citations1992Brij Masand, Gordon S. Linoff +1 more
A method for classifying news stories using Memory Based Reasoning (MBR) a k-nearest neighbor method, that does not require manual topic definitions, that is effective in reducing the development time to implement classification systems involving large number of topics for the purpose of classification, message routing etc.
The TIPSTER SUMMAC Text Summarization Evaluation
210 Citations1999Inderjeet Mani, David House +4 more
The TIPSTER Text Summarization Evaluation (SUMMAC) has established definitively that automatic text summarization is very effective in relevance assessment tasks.
Statistical models for topic segmentation
89 Citations1999Jeffrey C. Reynar
New clues that mark shifts to new topics, novel algorithms for identifying topic boundaries and the uses of such boundaries once identified are described.
A news story categorization system
72 Citations1988Philip J. Hayes, Laura Knecht +1 more
A pilot version of a commercial application of natural language processing techniques to the problem of categorizing news stories into broad topic categories based on fragmentary recognition using pattern-matching techniques is described.
Measuring the informativeness of a retrieval process
40 Citations1992Jean Tague‐Sutcliffe
A hypergraph-based framework for measuring the informativeness of a retrieval process is presented and a measure developed which satisfies the desired properties, including context sensitivity, user centrality, and logarithmic response.
Emerging Topic Tracking System
29 Citations2002Khoo Khyou Bun, Mitsuru Ishizuka
A system that track the changes to a particular area of a user's interests on the World Wide Web and to generate a summary of emerging topics back to the user, which is referred to as the Emerging Topic Tracking System (ETTS).