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Semantic algorithm

From Wikipedia, the free encyclopedia

Semantic algorithm is a computational engineering concept in computer science for information retrieval, and natural language processing. It uses the meaning of words, texts, or concepts, rather than exact word matching, to compare, find, classify, or infer information.[1][2] Primarily, it is used in writing for several families of methods that estimate semantic similarity, semantic relatedness, or query intent.[3]

Methods

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There is no single implementation of a semantic algorithm. Depending on the application, semantic information may be represented and processed using different methods.

  • Lexical methods use relationships between words, such as synonymy and hierarchical relationships, often obtained from lexical databases such as WordNet.[4]
  • Ontology-based methods uses the concepts and relationships within a particular domain and implement those representations for matching or inference.[2]
  • Structural methods use the organization and relationships between elements, such as the structure of database or XML schema.[4]
  • Hybrid methods combine several matching criteria or algorithms. It may combine lexical, structural, ontology-based, and user-feedback information.[4][5]
  • Semantic metadata and repositories associate algorithms with descriptions and domain information.[6]

Relation to other concepts

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A semantic algorithm should not be confused with semantic search, which is an application area concerned with retrieving information according to meaning or user intent. Semantic algorithms can be used to implement semantic-search systems, but the term itself is broader and has also been applied to schema matching, network synthesis, and software workflow generation.[7] The term is also distinct from semantics (computer science), which concerns with computational constructs. Similarly, semantic security is a specific concept in cryptography and is unrelated to the general use of the term semantic algorithm.[8]

See also

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References

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  1. Cacelja, F.; Trokanas, N; Raafat, T; Yu, M (1 May 2015). "Semantic Algorithm for Industrial Symbiosis Network Synthesis". openresearch.surrey.ac.uk. doi:10.1016/j.compchemeng.2015.04.031. Retrieved 2026-09-22.
  2. 1 2 Deepak, Gerard; Priyadarshini, J Sheeba; Babu, M S Hareesh (October 2016). "A differential semantic algorithm for query relevant web page recommendation". 2016 IEEE International Conference on Advances in Computer Applications (ICACA): 44–49. doi:10.1109/ICACA.2016.7887921.
  3. Shi, Lei; Mihalcea, Rada. "An Algorithm for Open Text Semantic Parsing" (PDF). University of North Texas via Association for Computational Linguistics.
  4. 1 2 3 Manakanatas, Dimitris; Plexousakis, Dimitris. "A Tool for Semi-Automated Semantic Schema Mapping: Design and Implementation" (PDF). Institute of Computer Science, FO.R.T.H. Institute of Computer Science, Foundation for Research & Technology – Hellas via CEUR Workshop Proceedings.
  5. "Leak Google Api.ContentWarehouse.V1 series : Une analyse technique Complète" [Leak Google Api.ContentWarehouse.V1 series: A Complete Technical Analysis]. BlackCat Montreal. 16 October 2024. Retrieved 22 September 2026.
  6. Dey, Sounak; Jaiswal, Dibyanshu; Paul, Himadri Sekhar; Mukherjee, Arijit (2016). Mandler, Benny; Marquez-Barja, Johann; Mitre Campista, Miguel Elias; Cagáňová, Dagmar; Chaouchi, Hakima; Zeadally, Sherali; Badra, Mohamad; Giordano, Stefano; Fazio, Maria (eds.). "A Semantic Algorithm Repository and Workflow Designer Tool: Signal Processing Use Case". Internet of Things. IoT Infrastructures. Cham: Springer International Publishing: 53–61. doi:10.1007/978-3-319-47075-7_7. ISBN 978-3-319-47075-7.{{cite journal}}: CS1 maint: periodical has ISBN (link)
  7. Duhan, Aryan; Singhal, Aryan; Sharma, Shourya; Neeraj; MK, Arti (2024-12-09), Semantic Search and Recommendation Algorithm, arXiv, doi:10.48550/arXiv.2412.06649, arXiv:2412.06649, retrieved 2026-09-22
  8. Stone, Mathew. "Semantics and Computational Semantics" (PDF). Rutgers University. Retrieved 22 September 2026.