Taxonomy for search engines
– A system for organizing and categorizing information in search engines.
– Helps improve search accuracy and efficiency.
– Provides a hierarchical structure for classifying web content.
– Enables users to navigate and filter search results more effectively.
– Used by search engines to understand the context and relevance of web pages.

Feature extraction
– The process of automatically extracting relevant features from data.
– In the context of search engines, it involves extracting meaningful information from web pages.
– Helps in indexing and categorizing web content.
– Can be based on various techniques such as natural language processing and machine learning.
– Important for improving search engine performance and user experience.

Internet search engines
– Web-based tools that allow users to search for information on the internet.
– Use algorithms to retrieve and rank relevant web pages.
– Play a crucial role in information retrieval and knowledge discovery.
– Google, Bing, and Yahoo are examples of popular search engines.
– Continuously evolving to provide more accurate and personalized search results.

References
– Vicient C, Sánchez D, Moreno A (2013). An automatic approach for ontology-based feature extraction from heterogeneous textual resources.
– Engineering Applications of Artificial Intelligence. 26 (3): 1092–1106. doi:10.1016/j.engappai.2012.08.002.
– Malina F, Piper I. Visual vocabulary suite, A vocabulary editor and content tagging extension.
– Unilexicon

See also
– Feature extraction
– Retrieved from https://en.wikipedia.org/w/index.php?title=Taxonomy_for_search_engines&oldid=1161157155
– Category: Internet search engines  Source: https://en.wikipedia.org/wiki/Taxonomy_for_search_engines

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