1 liveclassifier: creating hierarchical text classifiers through web corpora chien-chung huang...

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LiveClassifier: Creating Hierarchical Text Classifiers through Web Corpora

Chien-Chung HuangShui-Lung Chuang

Lee-Feng Chien

Presented by: Vu LONG

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Outline

1. Introduction

2. LiveClassifier

3. Evaluation

4. Contribution

5. Future work

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Introduction

http://140.109.19.252:8080/charles/index.jsp

• Uses Web search-result pages as the corpus

source• Exploits the structure information in the topic

hierarchy to train the classifier• Creates key terms to amend the insufficiency

of the topic hierarchy

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LiveClassifier (Demo version)

Classify documents

Computer Science Classifier is chosen

• There are three created classifiers (topics): Computer Science, Europe, Scientists based on Yahoo! directory

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LiveClassifier

Classify documents

Pseudo class

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LiveClassifier• Users can self create their classifiers

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LiveClassifier

• Feature Extractor

- Interacts with Search Engine and extracts highly-ranked search snippets as effective feature source

- Outputs feature vectors to describe both topic classes and text objects

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LiveClassifier• Hier-Concept-Query-Formulation

- Formulate query through the topic hierarchy

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LiveClassifier• Text Classifier

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Evaluation• Overall performance evaluation

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Evaluation• Granularity & Diversity

- Classifying text objects into different levels of the topic hierarchy got roughly the same results.

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Evaluation• Thematic Metadata for Textual Data

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Evaluation

• Paper Title Classification

- Collect data from 4 CS conferences in 2002

- Classify them into 36 second-level CS classes

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Contribution

• Finds the ways to collect and organize corpora effectively

• Creates key terms to amend the insufficiency of the topic hierarchy

• Classifies text objects automatically without a pre-labeled training set

• Cooperates with Web information services and other systems easily

• Helps to create more refined data (thematic metadata) for textual data

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Future work

• Optimize the classifier based by focusing on the training stage rather than only on organizing corpora

• Improve responding time

• Find appropriate pseudo classes