Enhancements in query evaluation and page summarization of The Thinking Algorithm

Abstract

This paper explores a unique way in which TheThinking Algorithm adds an extra logical substrate to a web search query using artificial intelligence. Instead of just going after keyword searching, the algorithm tries to assess the motives of the user behind entering a query. The algorithm tries to find the reasons as to why a user has entered a particular query by adding this question with every query: "Sitting in a particular region, why has the person entered such a query?" The Compounded Uniqueness Level applies the concept of geo-location searches. The algorithm allots competency level to the user from the query term using topic trees. The query parsers and indexers in the algorithm are more magnetized into extracting meaningful information from queries and web pages than just indexing the words present in a web page. Clustering the search results help to resolve the ambiguity in a user's query.

Compounded Uniqueness Level: Geo-Location Indexing Using Address Parser

“…In [3] Jansen and Spink showed that queries are shorter and therefore more ambiguous. However, work described here does not apply the Ambiguity Removal algorithm [1]. The main idea was to show the implementation of the C.U.L.…”

“…This research is a part of The Thinking Algorithm [1], which is a web search engine algorithm that adds the following question with every query: "Sitting in a particular region, WHY has the person entered such a query?" Compounded Uniqueness Level is a part of the algorithm that aids in geo-location searching and solves the first part of the above question.…”