🔍The search engine will be built using Rust programming language.
📚The indexer will parse XML files to create an index of the document corpus.
🔤The term frequency-inverse document frequency (TF-IDF) model will be used to rank search results.
🌐The search engine may be extended to support other file formats and implement additional features.
🚀Join us on this journey to build a search engine in Rust!
What is the purpose of this Azusian Session?
—The purpose of this Azusian Session is to develop a search engine in Rust using a document corpus and test case from the dogsGL website.
What programming language will be used to build the search engine?
—The search engine will be built using Rust programming language.
What is the indexer?
—The indexer is a component that parses XML files to create an index of the document corpus, allowing for efficient searching.
What is the TF-IDF model?
—The term frequency-inverse document frequency (TF-IDF) model is a technique used to rank search results based on the relevance of terms in documents.
Can the search engine be extended to support other file formats?
—Yes, the search engine can be extended to support other file formats and implement additional features.
00:00Introduction to the Azusian Session and the goal of building a search engine in Rust.
02:30Cloning the source code for the dogsGL website, which will be used as a test case for the search engine.
05:45Parsing XML files to create an index of the document corpus.
08:15Implementing the term frequency-inverse document frequency (TF-IDF) model to rank search results.
10:30Designing a simple search interface and discussing possible extensions for the search engine.
