Yoogli Semantic Search
Yoogli is a semantic search and computer science research Company. Yoogli is used to search Wikipedia, University Databases, Academic Journals, as well as millions of scholarly websites. Yoogli semantic search technology achieves more meaningful search results than keyword search results. It allows the user to create, collect and share personal collections with others on its website. The Company’s proprietary technology is protected under patents 7013300, 7219073, 7881981, and 8027876. The patents embody a locating, filtering, matching macro-context from a semantically indexed database for searching context and micro-context relevant to textual input by a user. Google purchased the patents in November 2011 through ICAP Patent Brokerage (now known as NEX Group) giving Yoogli a fully paid up worldwide license to develop and market the technology.
Yoogli search terms are converted into a semantic model. This model represents not the words, but their actual meaning. The semantic model of search terms is compared against the semantic models available in the global search space. The engine is able to understand and analyze complete pages of text, documents, and URLs. It is able to continuously drill down into a specific result thus refining the desired result for the user. Yoogli technology has the ability to represent people as semantic vectors, as well as specific interest groups that people form. This connects a user with other people with information that is most valuable and useful to them. The technology advances social networking to the next level. This allows people to find and access collection libraries that are of interest to them posted by other people. Collaborative filtering technology is able to identify people who have established themselves as experts in a particular field who may then be connected with others of like interests.
Semantic search technology improves accuracy by a deeper understanding of searcher intent and the contextual meaning of terms as they appear in the searchable database, whether on the Web or within a closed system, to generate more relevant results. Semantic search systems consider various points including the context of search, location, intent, the variation of words, synonyms, generalized and specialized queries, concept matching, and natural language processing queries to provide relevant search results. Using semantic search the user provides the search engine with a phrase, which is intended to denote an object about which the user is trying to gather information. There is no particular document, which the user knows about and is trying to get to. Rather, the user is trying to locate a number of documents, which together will provide the desired information. Semantic search is closely related to exploratory search. Yoogli semantic search uses semantics, or the science of meaning in language, to produce highly relevant search results. The goal is to deliver the information queried by a user rather than have a user sort through a list of loosely related keyword results.
The Yoogli semantic search algorithm is an automated computer program that continuously re-creates, re-masters and improves semantic search results for users. The algorithm is based on an analysis of each user's historical search footprint on a specific subject combined with all other searches on the same subject. The Yoogli algorithm learns from itself, continuously updates itself, and provides more perfected and more pinpointed search results to the user. In other words, Yoogli registered users may have a unique custom semantic search algorithm that understands and responds to specific search requests. This is based on both their own search footprint as well as the cumulative search footprints of thousands of other search users seeking the same information from their individual search queries.
The technology takes search technology to the next level in providing more pinpointed results for a user. It does this by adding and examining the behavioral paths that humans take using the technology in harnessing prior semantic search results to achieve more optimal search results against a specific subject of interest. The beginning of the search path that all users take begins when they choose "Similar Page Links" from the first Yoogli search result from the Yoogli database as the initial search result delivered to a user. This is the embodiment of semantic network intelligence, which is a precursor of semantic network artificial intelligence.
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