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Large Scale Search Engine for Text-Based dataset using positional inverted indexing and ranked retrievals

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Text-Based Dataset Search Engine

Welcome to the Text-Based Dataset Search Engine project! This search engine is designed to handle large-scale text-based datasets using positional inverted indexing and ranked retrievals. It offers powerful features to efficiently search and retrieve information from your dataset.

Key Features

1. Indexing Documents

  • User-Friendly: Our search engine is user-friendly and easy to use. It starts by asking the user for the name of the directory to index.
  • Document Loading: Once the directory is provided, the search engine loads all the documents in that directory.
  • Index Construction: It then constructs a positional inverted index with the contents of these documents. This index allows for fast and efficient searching.

2. Boolean Search Queries

  • Boolean Queries: Users can input Boolean search queries, allowing them to find documents that match specific criteria.
  • Powerful Filtering: This feature enables powerful filtering and retrieval of documents based on Boolean logic.

3. Ranked Retrieval Queries

  • Ranked Retrieval: The search engine also supports ranked retrieval queries.
  • Relevance Ranking: Users can search for documents based on relevance, and the engine will return results ranked by relevance.
  • Disk-Based Index: Ranked retrieval queries are processed on the disk-based inverted index, ensuring efficient performance even for large datasets.

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Large Scale Search Engine for Text-Based dataset using positional inverted indexing and ranked retrievals

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