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An Introduction to Information Extraction Techniques and Tools

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This report provides an overview of Information Extraction (IE), focusing on the methodologies and tools used to efficiently extract desired data from various sources. It explains the need for automated processes in handling abundant online data, which can be structured, semi-structured, or unstructured. The study explores wrapper induction and identification, highlighting techniques for extracting tuples from HTML and other data formats. This work aims to improve efficiency by reducing training data requirements and minimizing human error in data extraction tasks.

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An Introduction to Information Extraction Techniques and Tools

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    1. Information Extraction -Introduction and Tools V.G.Vinod Vydiswaran Roll no. 02329011 M.Tech (1st Year) KReSIT, IITBombay 29th October 2002 Guided by : Prof. S. Sarawagi

    2. 2 Introduction What is Information Extraction (IE) ? To select desired fields from the given data, by extracting common patterns that appear along with the information. To automate such a process. To make the process efficient by reducing the training data required, so as to restrict the cost.

    3. 3 Motivation Abundant online data available. Most IE systems specific to single information resource. IE models usually hand-coded, and hence error-prone. Data available either in structured form or in highly verbose content. Proper filters needed.

    4. 4 Types of Data Based on text styles: Structured data Semi-Structured text Plain text Based on information to the model: Labeled Unlabeled

    5. 5 Structured Data Relational Data Data in databases, in tables HTML Tags Query responses translated into Relational form using Wrappers Usually hand-coded and very specific to information resource

    6. 6 Wrapper Induction Wrapper Procedure extracting tuples from a particular information source A function from page to set of tuples Induction Task of generalizing from labeled examples to a hypothesis function of labeling instances

    7. 7 Wrapper Identification ExtractCCs (page P) { skip past first occurrence of <P> in P while next <B> is before next <HR> in P { for each (lk, rk) ? {(<B>,</B>), (<I>, </I>)} { skip past next occurrence of lk in P extract attribute from P to next occurrence of rk } } return extracted tuples } <HTML><HEAD> <TITLE>Country Codes</TITLE> </HEAD> <BODY> <B>Some Country Codes</B> <P> <B>Congo</B> <I>242</I><BR> <B>Egypt</B> <I>20</I><BR> <B>India</B> <I>91</I><BR> <B>Spain</B> <I>34</I><BR> <HR> <B>End</B> </BODY> </HTML>

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