Cognition Technologies has launched CognitionSearch, a linguistic search engine supporting synonymy, morphology and ontology, and at the same time, tapping one of the world's largest computational dictionaries known to man. With this approach, Cognition has become the advanced search engine for the LexisNexis Concordance service, a software service that is currently used today on 65,000+ desktops.
The combination of formal linguistic algorithms with semantic representations is at the core of Cognition's patented technology and combine to create a fast semantics via computational parsing. What makes this works is the use of 4.000.000 semantic representations, 350,000 word stems, 376,000 word senses or concepts, 17,000 ambiguous word definitions, 100,000 phrases, 7,000 nodes for the ontology or tree structure of the taxonomy, and 50,000 thesaural concept groups. Cognition's clients using the software are provided with tools to add their own specialized terminology. In the case of very large term expansions, Cognition will also supply them with a consulting service to augment the CognitionSearch service.
The Advanced Search mode will seem familiar to professional searchers with a lot of experience dealing with database services. The Advanced Search mode offers five basic search approaches: plain English search, linguistic Boolean search, quoted search, pattern search, and fuzzy search.
Search Engine Intelligence and SEO
There is a very distinctive focus in the current search engine algos towards AI. Google is the most obvious in the application of such technologies, but is not the only one. Some of the things search engines are utilizing in their machine learning process includes studying user behaviour, recording actions, drawing conclusions.
The more traditional ways that search engines have used previously to establish the populatiy of a given site, have been among others: volumen of inbound links, and their quality score based on relevancy of their anchor text and co-relation to the theme of the target sites. There are several factors involved in evaluating the links data that helps search engines to determine the popularity of a site and the importance of its content. In this new approach, the engines have been able to gain a finite amount of aggregate usage data from its various programs and services that allows them to further develop algos into more accurate and relevant services.
Nowadays, geotargeting or the personalisation of search results based on the geographic location of the users, browser-based and social bookmarking are just a few new elements added to the equation. Traffic source information to given search results also count. This allows search engines to really evaluate sites based on how popular they truly are, and weight their content and position in SERPs.
