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Machine learning based query term weight and synonym analyzer for query expansion. LucQE - open-source, Java. Provides a framework along with several implementations that allow to perform query expansion with the use of Apache Lucene. Xapian is an open-source search library which includes support for query expansion; ReQue open-source, Python ...
The Knowledge Query and Manipulation Language, or KQML, is a language and protocol for communication among software agents and knowledge-based systems. [1] It was developed in the early 1990s as part of the DARPA knowledge Sharing Effort, which was aimed at developing techniques for building large-scale knowledge bases which are share-able and re-usable.
A query language, also known as data query language or database query language (DQL), is a computer language used to make queries in databases and information systems. In database systems, query languages rely on strict theory to retrieve information. [1] A well known example is the Structured Query Language (SQL).
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...
Q serves as the query language for kdb+, a disk based and in-memory, column-based database. Kdb+ is based on the language k, a terse variant of the language APL. Q is a thin wrapper around k, providing a more readable, English-like interface. One of the use cases is financial time series analysis, as one could do inexact time matches.
An open-source, math-aware, question answering system called MathQA, based on Ask Platypus and Wikidata, was published in 2018. [15] MathQA takes an English or Hindi natural language question as input and returns a mathematical formula retrieved from Wikidata as a succinct answer, translated into a computable form that allows the user to insert ...
Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query.
Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.