multilayer som with tree-structured data for efficient document retrieval and plagiarism detection

Intelligent Database Systems Lab

國立雲林科技大學National Yunlin University of Science and Technology

Multilayer SOM With Tree-Structured Data for Efficient Document Retrieval and Plagiarism Detection

Presenter : Cheng-Feng Weng

Authors :Tommy W. S. Chow, M. K. M. Rahman

2009/10/12

TNN.18 (2009)

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Outline

Motivation Objective Method Experiments Conclusion Comments

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Motivation

Document Retrieval: Term-Frequency Problem

Two doc. Containing similar term frequencies may be of different contextually when it spatial distribution of terms is very different.

Plagiarism Detective: Paraphrasing Problem

SOM…project……..

SOM…be mapped into……..

Science…….Computer…….School……..

School of Computer Science……..

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Objective It proposed a tree-structured

document model with MLSOM for DR and PD.

Document…….

DR

PD

Global View

Local View

Tree-Structured Model

MLSOM

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Structured Representation of DF

A document is partitioned into pages that are further partitioned into paragraphs.

我是網頁第一行第二行無言的第三行

<HTML> <HEAD></HEAD> <BODY> 我是網頁 第一行 第二行 無言的第三行 </BODY></HTML>

我是網頁

第一行

第二行

無言的第三行

Page

我是網頁

第一行

Paragraph

我是網頁

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Structured Representation of DF (cont.)

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Multilayer SOM

MLSOM was developed for handling tree-structured data.

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Multilayer SOM (cont.)

Similarity:

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MLSOM Retrieval

Document

Trained MLSOM

Extract to tree-structure and project with PCA matrix

Related Docs.

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Plagiarism Detective

Plagiarism Detective using Local Association (PDLA)

Layer 3 SOM

D1, D2, …

D3, D4, ….

D2, D6, …

…

Related Docs.

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Experiments

Document Retrieval:

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Experiments (cont.)

Plagiarism Detective:

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Conclusions

A new approach of DR and PD using tree-structured document representation and MLSOM is proposed. It has shown that tree-structured representation

enhances the retrieval accuracy by incorporating local characteristics with traditional global characteristics.

Computational Issue: The MLSOM serves as an efficient computational

solution for practical implementation.

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Comments

Advantage Practical, Simple but efficient and effective

Drawback Rate of fail plagiarism detective is still high

Application …

multilayer som with tree-structured data for efficient document retrieval and plagiarism detection

Documents