Accuracy barrier - An accuracy barrier is a proposed limit to predictive accuracy arising from variability or uncertainty in what is being predicted.
Ad hoc retrieval - Ad hoc retrieval is the information-retrieval task of finding documents relevant to a user's current information need in response to a query.
Algorithmic amplification - Algorithmic amplification is an increase in the visibility or distribution of content associated with an algorithmic selection or ranking process relative...
Average node degree - Average node degree is the arithmetic mean of the degrees of all nodes in a graph.
Average reward - Average reward is a reinforcement-learning objective that evaluates a policy by its long-run expected reward per time step.
Binary independence model - The Binary Independence Model is a probabilistic information-retrieval model that ranks documents using binary indicators of term presence and a conditional...
Biword index - A biword index is a search index whose entries represent pairs of consecutive terms.
Blocked sort-based indexing - Blocked sort-based indexing (BSBI) is a method for constructing an inverted search index when all intermediate term-document data cannot comfortably fit in...
BM25 - BM25 is a ranking method for text retrieval that scores documents using query-term matches, term rarity, term frequency and document length.
Caverphone - Caverphone is a phonetic coding algorithm that converts a written name or word into a compact code intended to help find similar-sounding spellings.
Cluster labeling - Cluster labeling is the process of assigning a human-readable description to a group of similar items.
Cold start (recommender systems) - Cold start in recommender systems is the difficulty of making useful recommendations when there is little or no relevant interaction history.
Cologne phonetics - Cologne phonetics, also called Kölner Phonetik, is a phonetic coding method designed for German-language text.
Compound-term processing - Compound-term processing is an information-retrieval approach that recognizes and uses combinations of words as meaningful units instead of relying only on...
Contextual embeddings - Contextual embeddings are numerical representations whose values depend on the surrounding input.
Contextual searching - Contextual searching uses information about the situation surrounding a query to help interpret the user's need and retrieve or rank results.
Controlled vocabulary - A controlled vocabulary is a managed set of terms used consistently to describe, index or organize information.
Coverage error - Coverage error is a measure of how far down a ranked list of labels a system must go to include every correct label for an example.
Daitch-Mokotoff Soundex - Daitch-Mokotoff Soundex is a phonetic name-coding system developed by Randy Daitch and Gary Mokotoff.
Divergence-from-randomness model - A divergence-from-randomness model is an information-retrieval model that weights query terms according to how their occurrence in a document departs from a...
Document-at-a-time - Document-at-a-time is a search-query evaluation strategy that combines the contributions of query terms for one document before moving to another document.
Document clustering - Document clustering is the process of grouping documents according to patterns of similarity in their representations.
Document partitioning - Document partitioning divides a search collection into subsets of documents and maintains a local index for each subset.
Double moving average - A double moving average is a moving average applied to a series that has already been smoothed by a moving average.
Embedding - An embedding is a numerical representation that places an item in a vector space where relationships can be useful for a machine-learning task.
Embedding matrix - An embedding matrix is a table of numerical vectors, typically with one row for each token or category and one column for each embedding dimension.
Embedding space - An embedding space is the vector space in which a model represents items as numerical coordinates.
Embedding vector - An embedding vector is an ordered list of numerical coordinates representing an item for a machine-learning task.
Extended Boolean model - The extended Boolean model is an information-retrieval approach that combines structured Boolean-style queries with weighted matching and ranked results.
Faceted search - Faceted search is a search approach that lets users narrow results through several organized attributes, called facets.
Federated averaging - Federated averaging, often shortened to FedAvg, is a federated-learning algorithm that combines locally trained model parameters into a shared model.
Feed forward chunking - Feed forward chunking is a memory-management technique that processes a transformer's position-wise feed-forward computation in smaller groups of token...
Fuzzy retrieval - Fuzzy retrieval is an information-retrieval approach that represents degrees of match rather than only yes-or-no membership.
Hashtag - A hashtag is a label formed by placing the hash symbol, #, before a word or unspaced phrase in a service that recognizes this syntax.
Implicit data collection - Implicit data collection is the gathering of behavioral traces that can be used to infer user interests, preferences or needs without asking for a direct...
Information retrieval - Information retrieval is the process of finding material that addresses an information need within a collection.
Inverted index - An inverted index is a search data structure that maps terms to the documents or records in which they occur.
Item-item collaborative filtering - Item-item collaborative filtering is a recommendation approach that uses relationships between items inferred from users' interactions or ratings.
Learned sparse retrieval - Learned sparse retrieval is a family of search methods that train models to produce sparse representations for matching queries and documents.
Literature-based discovery - Literature-based discovery is the use of published research to identify potentially new connections or hypotheses by bringing together findings that have...
Location-based recommendation - Location-based recommendation is the selection or ranking of suggested items using geographical context as part of the decision.
Long tail - The long tail is the large collection of relatively infrequent items or events beyond a small group of highly popular ones in a ranked distribution.
Low-dimensional embedding - A low-dimensional embedding represents an item using relatively few numerical coordinates while aiming to retain relationships useful for a task.
Macroaveraging - Macroaveraging combines evaluation results by calculating a metric separately for each class or other defined unit and then taking their unweighted...
Match rating approach - The Match rating approach (MRA) is a rule-based method for comparing names through compact phonetic encodings and a rating procedure.
Metaphone - Metaphone is a phonetic encoding algorithm that converts a word into a compact code using spelling rules intended to approximate aspects of its pronunciation.
Microaveraging - Microaveraging combines evaluation evidence across classes or labels before calculating the final metric.