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Mini Project 3

The document describes implementing the Block-Sorted Based Indexing (BSBI) algorithm to build an efficient inverted index for information retrieval. Key steps include preprocessing documents, indexing terms, merging intermediate index blocks, and incorporating gamma coding to optimize storage of document identifiers. The project involves understanding and applying the BSBI algorithm through functions for preprocessing, indexing, and gamma coding, and reporting on findings, challenges, and insights from the implementation experience.

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33 views1 page

Mini Project 3

The document describes implementing the Block-Sorted Based Indexing (BSBI) algorithm to build an efficient inverted index for information retrieval. Key steps include preprocessing documents, indexing terms, merging intermediate index blocks, and incorporating gamma coding to optimize storage of document identifiers. The project involves understanding and applying the BSBI algorithm through functions for preprocessing, indexing, and gamma coding, and reporting on findings, challenges, and insights from the implementation experience.

Uploaded by

m2000.h1379
Copyright
© © All Rights Reserved
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Implementing the BSBI Algorithm for Inverted Indexing

About
This project centers on constructing an Information Retrieval (IR) system using the Block-Sorted Based Indexing
(BSBI) algorithm. The BSBI algorithm facilitates the creation of an inverted index from a collection of text documents,
and the objective is to implement key steps, including document preprocessing, term indexing, and the merging
of intermediate index blocks. As an additional focus, students will incorporate gamma coding into the inverted
index construction process. Gamma coding, a variable-length coding technique, will optimize the representation of
positive integers, improving storage efficiency and speeding up information retrieval, particularly for datasets with
skewed distributions where smaller values are more common. This addition provides practical exposure to advanced
compression techniques within the context of building an efficient Information Retrieval system.here

Project Overview
Your task is to understand and implement the BSBI algorithm, encompassing the processing of text documents,
creating an inverted index, and managing intermediate index blocks. The project is structured to provide hands-on
experience in information retrieval and the nuances of building inverted indexes. In particular, during the implemen-
tation of the inverted index, it is recommended to utilize gamma coding. Rather than encoding the absolute number
of documents, the emphasis should be on gamma encoding the differences between document IDs. Here are the key
components and functionalities:

• Document Preprocessing:Document Preprocessing: Begin by reading and preprocessing the text documents.
This includes converting documents into a word list, tokenization, punctuation removal, and stemming.

• Inverted Index: Implement the core BSBI algorithm to build an inverted index. This involves processing
documents, indexing terms, and preparing them for later merging.
• Gamma Coding for Document ID Gaps: Integrate gamma coding into the inverted index implementation.
Use gamma coding to encode the differences or gaps between document IDs.

• Index Block Merging: Implement the merging of intermediate index blocks to create a final inverted index.
The merging process is critical for handling large document collections efficiently.
• Implement Bit Manipulation for Gamma Coding(Optional) For an advanced implementation, consider
utilizing bit manipulation techniques to implement gamma coding.

Deliverables
• Functions or methods for handling document preprocessing, building an inverted index, and implementing gamma
coding. We would appreciate the addition of comments to enhance understanding for reviewers during the
correction process.

• A report summarizing key findings, challenges faced, and insights gained during the project, with a specific focus
on the process of implementing the BSBI algorithm.

References
Document and reference the sources, libraries, and tools used in the project. You can refer to the NLTK library for
text processing and explore relevant literature on Information Retrieval techniques.

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