Information Retrieval

BM25 is a ranking function used by search engines to evaluate the relevance of documents to a query.

Cross-Lingual Information Retrieval (CLIR) enables search across multiple languages using AI techniques.

Cross-Modal Retrieval is the process of finding information across different data types, like images and text.

Dense Retrieval is an information retrieval method that uses high-dimensional embeddings to find relevant data efficiently.

Document Retrieval is the process of identifying and extracting relevant documents from a database or collection based on user queries.

Entity Linking connects text mentions to their corresponding real-world entities in databases.

Expected Reciprocal Rank (ERR) measures the effectiveness of ranked retrieval systems based on user satisfaction.

The Gopher Model is a framework for organizing and retrieving information on the internet using a hierarchical structure.

A haystack is a large mound of hay, often used metaphorically to describe searching for something difficult to find.

Image Retrieval is the process of obtaining images from a database based on user queries.

In-context retrieval is a method where an AI system finds relevant information based on the current context of a query.

Intelligent Search uses AI to enhance search results by understanding context, intent, and user preferences.

An inverted index is a data structure used to improve the speed of text retrieval operations in search engines.

Keyword extraction is the process of identifying and extracting important words or phrases from text.

A Knowledge Graph is a structured representation of information that connects concepts and entities in a meaningful way.

Listwise ranking is a method for organizing items based on their relevance to a query, considering the entire list of items.

Mean Reciprocal Rank (MRR) measures the effectiveness of systems in returning relevant results in ranked lists.

Multi-Modal Retrieval refers to the process of searching and retrieving information across different types of data, like text, images, and audio.

A Needle-in-a-Haystack Test evaluates an AI's ability to find rare or hidden information within a large dataset.

Open Source Intelligence (OSINT) involves collecting and analyzing publicly available information for security and decision-making.

Query expansion is a technique to improve search results by enhancing user queries with additional terms.

Query rewriting is the process of transforming a user's query into a format that optimizes search results.

Re-ranking is the process of adjusting the order of search results or recommendations based on additional criteria.

Retrieval-Augmented Generation combines information retrieval with natural language generation to enhance content creation.

Stemming is a text normalization process that reduces words to their base or root form.

Table extraction is the process of identifying and retrieving data from tables in documents or web pages.

TF-IDF is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents.