A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

Abstract

This paper presents an approach for the Opinion Finding task at TREC 2008 Blog Track. For the Ad-hoc Retrieval subtask, we adopt language model to retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach to predict and rank opinionated documents are the focuses of our participation this year. Regarding the hybrid method for opinion retrieval subtask, our submitted runs yield 15% improvement over baseline.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2008
Accession Number
ADA512749

Entities

People

  • Gumwon Hong
  • Hae-chang Rim
  • Joo-young Lee
  • Linh Hoang
  • Seung-wook Lee

Organizations

  • Korea University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Base Lines
  • Classification
  • Dictionaries
  • Electronic Mail
  • Feedback
  • Filtration
  • Information Operations
  • Language
  • Learning
  • Machine Learning
  • Natural Language Processing
  • Natural Languages
  • Online Communications
  • Operating Systems
  • Standards
  • Word Lists

Fields of Study

  • Computer science

Readers

  • Information Retrieval
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Information Retrieval
  • AI & ML - Neural Networks