Web Search System

A Web Search System is a search system can solve a Web search task by applying a web search algorithm.

• AKA: Web IR Technique, Internet Search System, Web Query System.
• Context:
  • It can range from being a General Web Search System to being a Domain-Specific Web Search System.
  • It can be a system used by a Web Search Service.
  • It can be based on a Document Search Platform.
  • …
• Example(s):
  • Google Web Search System,
  • Bing Web Search System,
  • a Domain-Specific Web Search System, such those that support Google Scholar Search and Google Blog Search Service.
  • a Semantic Web Search System.
  • …
• Counter-Example(s):
  • a Database Search System,
  • an offline Repository Search System,
  • a Question Answering System,
  • a Web Hosting System,
  • an Intranet IR System,
  • a Web Directory,
  • an Ontology Search System.
• See: Keyword Search System, Link Analysis Algorithm, Information Retrieval, Search Engine Results Page, Web Page.

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References

2017

• (Martin, 2017) ⇒ Eric Martin (2017). "Search Engines: Applications of ML". In: Sammut & Webb (2017). DOI: 10.1007/978-1-4899-7687-1_750
  • QUOTE: The general structure of a search engine is described. An overview of those information retrieval methods that are relevant to web search in that they take the existence of hyperlinks between documents into account, is provided. A suggested classification of web queries as either navigational, transactional, or informational has been suggested. More generally, a good understanding of users’ needs and practice allows for query rewriting or for redirection to domain-specific databases.

2015

• (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/web_search_engine Retrieved:2015-12-17.
  • A web search engine is a software system that is designed to search for information on the World Wide Web. The search results are generally presented in a line of results often referred to as search engine results pages (SERPs). The information may be a mix of web pages, images, and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories, which are maintained only by human editors, search engines also maintain real-time information by running an algorithm on a web crawler.

2011

• (Mukhopadhyay et al., 2011) ⇒ Debajyoti Mukhopadhyay, Aritra Banik, Sreemoyee Mukherjee, Jhilik Bhattacharya, and Young-Chon Kim. (2011). “A Domain Specific Ontology Based Semantic Web Search Engine.” In: Proceedings of 7th International Workshop on MSPT (MSPT 2007).
  • QUOTE: In 2006, some users found major search-engines became slower to index new Web-pages. Keyword searches have a tough time distinguishing between words that are spelled the same way, but mean something different. This owten results in hits that are completely irrelevant to the query.
    • Some search engines also have trouble with stemming, i.e., if the word " big" is entered, should it return a hit on the word, " bigger? " What about singular and plural words? What about verb tenses that differ from the word someone entered by only an " s" or an "ed"?
    • Search engines also cannot return hits on keywords that mean the same, but are not actually entered in the query. A query on heart disease would not return a document that used the word "cardiac" instead of "heart".
    • Users are returned thousands to millions of Web pages in return of their queries, of which majority prove to be irrelevant to the query submitted and is impossible for any user to go through.

In view of the above mentioned problems, come up the concept of semantic Web and semantic Web search engines.

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