METHOD FOR RANKING RESOURCES USING NODE POOL
An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.
1 . A search engine comprising:
a. a search process using correlation, and
b. an input evaluation function for extracting inputs for the search process from user supplied input and providing the inputs for the search to the search process.
2 . The search engine of claim 1 in which the input evaluation function comprises a subject evaluation function for extracting subject information from keywords, phrases, sentences, concepts, compound, complex or orthogonal inputs or a simple web query and passing the subject information to the search process.
3 . The search engine of claim 2 in which the subject evaluation function for keywords and phrases comprises a pass through function.
4 . The search engine of claim 2 in which the subject evaluation function for sentences comprises a natural language parser.
5 . The search engine of claim 2 in which the subject evaluation function for concepts comprises subject, object and optionally context information.
6 . The search engine of claim 2 in which the subject evaluation function for compound, complex or orthogonal inputs comprises a clause recognition function and a natural language parser.
7 . The search engine of claim 2 in which the subject evaluation function for a simple web query comprises a phrase recognition process.
8 . The search engine of claim 1 in which the input comprises a digital information object and the input evaluation function comprises a topic detection module adapter and a topic detection module.
9 . The search engine of claim 8 further comprising a natural language parser receiving the output of the topic detection module.
10 . The search engine of claim 1 in which the input comprises a question generation function for defining a query.
11 . The search engine of claim 10 in which the question generation function creates a static menu of questions.
12 . The search engine of claim 10 in which the question generation function creates a dynamic menu of questions.
13 . The search engine of claim 10 in which the query is presented in a canonical form.
14 . The search engine of claim 1 in which the output of the search process is based on an answer space.
15 . The search engine of claim 14 in which the output of the search process is strongly associated with resources identified from the answer space.
16 . The search engine of claim 14 in which the output is strongly associated with resources used to create the answer space.
17 . The search engine of claim 14 in which the output is transitively associated with the user input through resources used to create the answer space.
18 . The search engine of claim 14 in which relevancy of the resources to the user input is guaranteed by the existence of an answer space.
19 . The search engine of claim 14 , which does not use a similarity measure to establish relevancy.
20 . The search engine of claim 1 in which the output of the search process is applied to a post search process for determining the order of presentation to a user.