Knowledge correlation search engine
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 method comprising:
obtaining, by a computer, inputs of a search from a user;
determining, by the computer, a plurality of logical structures associated with the search within one or more collections of data objects, wherein determining the plurality of logical structures comprises:
determining the plurality of resources by identifying one or more information sources relevant to the inputs of the search,
determining a plurality of nodes using information obtained from the plurality of resources, and
determining one or more correlations between the inputs of the search and the data objects based on the plurality of nodes;
determining a subset of data objects, within the one or more collection of data objects, that are members of the plurality of logical structures, the subset of data objects forming an answer space and being associated with a respective plurality of resources that contributed to the subset of data objects and the answer space;
determining, by the computer, resource identifiers of the plurality of resources; and
providing by the computer, the resource identifiers of the plurality of resources to the user.
2. The method of claim 1 , wherein the inputs of the search comprise at least two parameters lacking lexical overlap or semantic overlap.
3. The method of claim 2 , wherein the plurality logical structures represent correlations between the at least two parameters in the plurality of resources.
4. The method of 3 , wherein the at least two parameters comprise an origin of the search and a destination of the search.
5. The method of claim 4 , wherein determining the plurality of logical structures comprises modeling the correlations using a plurality of paths of nodes between a first node corresponding to the origin of the search and a second node corresponding to the destination of the search.
6. The method of claim 1 , wherein determining the plurality of logical structures comprises obtaining the data objects from one or more of a set of information sources consisting of the following: a computer file system, the Internet, a relational database computer, an email computer, a taxonomy computer, and an ontology computer.
7. The method of claim 1 , wherein the one or more correlations comprise one or more chains of the plurality of nodes.
8. The method of claim 1 , wherein the one or more chains of the plurality of nodes comprise an acyclic graph.
9. The method of claim 1 , further comprising displaying the one or more correlations using a hierarchical layout by assigning the plurality of nodes to different layers.
10. The method of claim 1 , wherein the resource identifiers are uniform resource locators (URLs).
11. The method of claim 1 , further comprising determining, based on the inputs of the search, whether to use a conventional search engine.
12. A non-transitory computer-readable storage media storing program instructions that, when executed by a computer, cause the computer to perform operations comprising:
obtaining inputs of a search from a user;
determining a plurality of logical structures associated with the search within one or more collections of data objects, wherein determining the plurality of logical structures comprises:
determining the plurality of resources by identifying one or more information sources relevant to the inputs of the search,
determining a plurality of nodes using information obtained from the plurality of resources, and
determining one or more correlations between the inputs of the search and the data objects based on the plurality of nodes;
determining a subset of data objects, within the one or more collection of data objects, that are members of the plurality of logical structures, the subset of data objects forming an answer space and being associated with a respective plurality of resources that contributed to the subset of data objects and the answer space;
determining resource identifiers of the plurality of resources; and
providing the resource identifiers of the plurality of resources to the user.
13. The computer readable storage media of claim 12 , wherein the inputs of the search comprise at least two parameters lacking lexical overlap or semantic overlap.
14. The computer readable storage media of claim 13 , wherein the plurality logical structures represent correlations between the at least two parameters in the plurality of resources.
15. The computer readable storage media of 14 , wherein the at least two parameters comprise an origin of the search and a destination of the search.
16. The computer readable storage media of claim 15 , wherein determining the plurality of logical structures comprises modeling the correlations using a plurality of paths of nodes between a first node corresponding to the origin of the search and a second node corresponding to the destination of the search.
17. The computer readable storage media of claim 12 , wherein determining the plurality of logical structures comprises obtaining the data objects from one or more of a set of information sources consisting of the following: a computer file system, the Internet, a relational database computer, an email computer, a taxonomy computer, and an ontology computer.
18. The computer readable storage media of claim 12 , wherein the one or more correlations comprise one or more chains of the plurality of nodes.
19. The computer readable storage media of claim 12 , wherein the one or more chains of the plurality of nodes comprise an acyclic graph.
20. The computer readable storage media of claim 12 , wherein the operations further comprise displaying the one or more correlations using a hierarchical layout by assigning the plurality of nodes to different layers.
21. The computer readable storage media of claim 12 , wherein the resource identifiers are uniform resource locators (URLs).
22. The computer readable storage media of claim 12 , wherein the operations further comprise determining, based on the inputs of the search, whether to use a conventional search engine.