InvertedSearch is a tool designed to optimize search functionality by utilizing an inverted index data structure. This approach enables rapid full-text searches by mapping words to their locations within a set of documents. Instead of scanning every document, the system uses an index to quickly locate relevant files, significantly improving search speed and efficiency.
- Optimize Search Performance: By creating an efficient inverted index, the system reduces the time and resources needed to find documents that contain specific words.
- Enable Fast Querying: Implement a robust querying mechanism that provides quick results by leveraging the pre-built index.
- Maintain Flexibility: Allow for easy updating of the index as files are added or removed from the database.
- Hashing: Understanding of hash tables for efficient data retrieval.
- Single Linked List: Basic knowledge of linked lists for storing and managing index data.
An inverted index maps content (such as words) to its locations in a database or set of documents, allowing for rapid full-text searches. This data structure is fundamental in search engines and document retrieval systems. While building the index involves some overhead, it greatly enhances search query performance.
- Indexing: Create and maintain an index of words from a set of files.
- Searching: Efficiently query the indexed data to find relevant documents based on user input.
- Inverted Index - Wikipedia
- Stanford IR Book - Building an Inverted Index
- IJCSI - Inverted Index
- ElasticSearch - Inverted Index
- Quora - Information Retrieval and Inverted Index
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