System and methods for searching objects and providing answers to queries using association data

• US 9,367,608 B1
• Filed: 03/16/2014
• Issued: 06/14/2016
• Est. Priority Date: 01/07/2009
• Status: Expired due to Fees

• Current Assignee: Linfo IP LLC (Pueblo Nuevo LLC)
• Original Assignee: Guangsheng Zhang
• Inventors: Zhang, Guangsheng
• Primary Examiner(s): Ho, Binh V
• Application Number:
  US14/214,955
• Time in Patent Office: 821 Days
• Field of Search: 707/730
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/3331 Query processing
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

System and methods are disclosed for providing answers to search queries, and for searching using association data without requiring keyword matching. Datasets representing objects and their properties are created from unstructured data sources based on natural language analysis methods, and can be used to answer queries about objects or properties of objects. Implementations include general information search engines and embodiments for searching products, services, people, or other objects without knowing the names of such objects, or searching for information about known objects by using either keyword-based queries or natural language queries such as asking questions. System and methods are also provided for creating a structured or semi-structured representation of various unstructured data, in contrast to the conventional term-vector or term-document matrix representation.

Claims

1. A computer-implemented method for searching information, comprising:

receiving a query in a non-structured query language format comprising a text format or speech format;

identifying a first term in the query;

receiving an object-specific dataset associated with an object, wherein the object includes a physical or conceptual object or an object class, wherein the object and the object-specific dataset are associated with a name or description represented by a second term, wherein the object-specific dataset contains at least a third term, wherein the third term represents a name of a property associated with the object, or represents a term associated with the second term, wherein the third term is obtained from a text content containing a sentence associated with the second term using an automated text analysis method, wherein the third term is associated with an importance measure, the importance measure indicating the importance of the property in relation to the object, or serving as a criterion for including the third term as a term in the object-specific dataset;

comparing the first term with the third term;

if the first term matches the third term,

selecting the second term; and

outputting, in a text or speech format, the second term representing the object name or description at least in part as an answer to the query.

2. The method of claim 1, wherein the object is a product or service or a person or an organization, wherein the property is a feature or function or attribute of the product or service or person or organization.

3. The method of claim 1, wherein two or more object-specific datasets are received, and the first term matches a third term in two or more object-specific datasets, and wherein two or more second terms representing two or more object names or descriptions are output as answers to the query, the method further comprising:

ranking the two or more object names or descriptions based on the importance measure.

4. The method of claim 1, wherein the automated text analysis identifies the grammatical attributes of the terms in the sentence, wherein the grammatical attributes include grammatical roles and parts of speech associated with a term in the sentence.

5. The method of claim 4, wherein the grammatical roles of the terms in the sentence include a grammatical subject, a predicate comprising the non-subject portion of the sentence, a multi-word phrase, a sub-component in a multi-word phrase, a head in a phrase, and a modifier in a phrase.

6. The method of claim 5, wherein the second term is a term associated with the grammatical role of a subject of a sentence, wherein the third term is a term associated with the grammatical role of a predicate or part of a predicate comprising the non-subject portion of the sentence.

7. The method of claim 1, wherein the importance measure of the third term is determined based on the frequency of the third term associated with the second term.

8. The method of claim 1, wherein the importance measure of the third term is determined based on the contextual attributes of the third term, wherein the contextual attributes include grammatical, semantic, and positional attributes associated with the third term.

9. The method of claim 1, further comprising:

identifying the first term in the query as a term representing a property associated with an object based on a grammatical role associated with the first term, wherein the grammatical role includes the first term being in a non-subject portion of a sentence in the query.

10. A computer-implemented method for searching information, comprising:

receiving a query in a non-structured query language format comprising a text format or speech format;

identifying a first term in the query;

receiving an object-specific dataset associated with an object, wherein the object includes a physical or conceptual object or an object class, wherein the object and the object-specific dataset are associated with a name or description represented by a second term, wherein the object-specific dataset contains at least a third term, wherein the third term represents a name of a property associated with the object, or represents a term associated with the second term, wherein the third term is obtained from a text content containing a sentence associated with the second term using an automated text analysis method, wherein the third term is associated with an importance measure, the importance measure indicating the importance of the property in relation to the object, or serving as a criterion for including the third term as a term in the object-specific dataset;

comparing the first term with the second term;

if the first term matches the second term,

selecting the third term; and

outputting, in a text or speech format the third term representing the property associated with the object at least in part as an answer to the query.

11. The method of claim 10, further comprising:

outputting a description of the object based on the selected property names.

12. The method of claim 10, wherein the importance measure of the third term is determined based on the frequency of the third term associated with the second term.

13. The method of claim 10, wherein the automated text analysis identifies the grammatical attributes of the terms in the sentence, wherein the grammatical attributes include grammatical roles and parts of speech associated with a term in the sentence.

14. The method of claim 13, wherein the grammatical roles of the terms in the sentence include a grammatical subject, a predicate comprising the non-subject portion of the sentence, a multi-word phrase, a sub-component in a multi-word phrase, a head in a phrase, and a modifier in a phrase.

15. The method of claim 14, wherein the second term is a term associated with the grammatical role of a subject of a sentence, wherein the third term is a term associated with the grammatical role of a predicate or part of a predicate comprising the non-subject portion of the sentence.

16. The method of claim 10, wherein the importance measure of the third term is determined based on the frequency of the third term associated with the second term.

17. The method of claim 10, wherein the importance measure of the third term is determined based on the contextual attributes of the third term associated with the second term, wherein the contextual attributes include grammatical, semantic, and positional attributes associated with the third term.

18. The method of claim 10, further comprising:

identifying the first term in the query as a term representing an object based on a grammatical role associated with the first term, wherein the grammatical role includes the first term being a grammatical subject of a sentence in the query.