Method for facet searching and search suggestions

• US 9,424,294 B2
• Filed: 12/02/2014
• Issued: 08/23/2016
• Est. Priority Date: 12/02/2013
• Status: Active Grant

• Current Assignee: Finch Computing LLC (Qbase, LLC)
• Original Assignee: Qbase, LLC
• Inventors: Lightner, Scott, Weckesser, Franz
• Primary Examiner(s): PHILLIPS, III, ALBERT M
• Application Number:
  US14/557,807
• Publication Number:
  US 20150154264A1
• Time in Patent Office: 630 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2468 Fuzzy queries
• CPC Class Codes: G06F 16/90324 using system suggestions
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06F 16/9038 Presentation of query results

Abstract

Methods for faceted searching within clustered in-memory databases are disclosed. Faceted searching may be used to generate search suggestions. The faceted search engine may be able to use non-literal key algorithms for a partial prefix fuzzy matching and may include a feature disambiguation module. The disclosed search engine may be capable of processing large amounts of unstructured data in real time to generate search suggestions.

Claims

1. A method comprising:

receiving one or more first search queries;

processing fields in the one or more first search queries wherein the processing comprises at least one of address standardization, proximity boundaries, nickname interpretation, extraction of at least prefix, and generation of at least one non-literal key;

constructing one or more second search queries associated with the one or more first search queries wherein the one or more second search queries are stack-based;

sending the one or more second search queries to one or more search conductors wherein the one or more search conductors are associated with collections specified in the one or more second search queries;

scoring a match of one or more fields of one or more records against the one or more second search queries;

adding the one or more records to a results list based on the scoring;

continually scoring the one or more records until all records in a partition have been processed;

sorting the results list;

receiving and collating the results list;

performing aggregate analytics processing on the results list wherein the aggregate analytics processing comprises extracting, disambiguating, normalizing, grouping, and indexing a first set of facets from documents wherein the facets comprise different levels of specificity;

returning results of the aggregate analytics processing;

storing the results in a knowledge base wherein the knowledge base is part of an in-memory database system architecture;

loading new documents into an in-memory database;

extracting a second set of disambiguated facets from the new documents; and

comparing the second set of disambiguated facets with the first set of disambiguated facets wherein the comparing comprises;

updating the knowledge base and returning the ID of matching facets; and

assigning a unique ID to unmatched facets, associating the unmatched facets with a cluster of defining features, and storing the unmatched facets and the cluster in the knowledge base.

2. The method according to claim 1, wherein the one or more first search queries are represented in at least one markup language selected from a group consisting of XML and HTML.

3. The method according to claim 1, wherein the one or more first search queries are represented in a compact format or a binary format.

4. The method according to claim 1, further comprising parsing the one or more first search queries to determine if the processing of the one or more first search queries is required or not.

5. The method according to claim 1, further comprising determining whether the score is more or less than a pre-defined acceptance threshold.

6. The method according to claim 5, wherein the pre-defined acceptance threshold is defined in a search query.

7. The method according to claim 5, wherein the pre-defined acceptance threshold is a default value.

8. The method according to claim 5, wherein the pre-defined acceptance threshold varies according to the one or more fields being scored.

9. The method according to claim 5, wherein the one or more records are added to the result list when the score are more than the pre-defined acceptance threshold.

10. The method according to claim 1, wherein the results list are returned asynchronously.

11. The method according to claim 1, further comprising performing analytic processing of the results list by one or more techniques.

12. The method according to claim 1, wherein the one or more techniques comprises rolling up several records into a complete records and determine information about neighbor records.

13. The method according to claim 1, wherein the facets are indexed according to a hierarchy.

14. The method according to claim 13, wherein the hierarchy is either pre-defined or defined by an administrator.

15. The method according to claim 13, wherein the facets at first level of hierarchy are broadest facets.

16. The method according to claim 13, wherein the facets are stored in collections.

17. The method according to claim 13, wherein each facet type in the facets is stored in a different collection or a group of collections.

18. The method according to claim 1, wherein the knowledge base is configured to temporarily store clusters of disambiguated facets and their related features.