Information Retrieval (IR) is the action/process of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the science of searching for information in a document, searching for documents themselves, searching for metadata that describes data and for databases such as text, image or sound. Automated information retrieval systems are used to reduce what has been called “information overload”. Many universities and public libraries use IR systems to provide access to books, journals, and other documents. Web search engines are the most visible IR applications. As far as IR is concerned, an object is an entity that is represented by information in a content collection or database. User queries are matched against the database information. However, as opposed to classical SQL queries of a database, in information retrieval the results returned may or may not match the query, so results are typically ranked. This ranking of results is a key difference of information retrieval searching compared to database searching. Depending on the application the data objects may be, for example, text documents, images, audio, mind maps or videos.
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Recommended reading list:
|Data Science from Scratch: First Principles with Python
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.
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