Method and system for scoring articles in an on-demand services environment

• US 9,280,596 B2
• Filed: 04/07/2011
• Issued: 03/08/2016
• Est. Priority Date: 07/01/2010
• Status: Active Grant

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Salesforce.com, Inc.
• Inventors: Rajagopal, Vinodh
• Primary Examiner(s): Yen, Syling
• Application Number:
  US13/082,299
• Publication Number:
  US 20120005218A1
• Time in Patent Office: 1,797 Days
• Field of Search: 707/736, 707/737, 707/748, 707/752, 707755-758, 707/781, 707/999.003, 715/736, 715/738, 715/854, 709/203
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/33 Querying
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

A method for scoring and ranking knowledge articles in an on-demand service environment in a database network system. The scoring allows users to have input into the scoring to determine relevancy and authenticity to solve particular problems.

Claims

1. A method comprising:

determining, by a host system of a database system, the host system having a processor system including one or more processors and a storage system, an increment to a score of an article based on;

at least one vote for the article, the at least one vote being weighted higher for votes from external users than votes from internal users, the internal users being internal with respect to an organization controlling the article, the external users being external with respect to the organization,

a reference to the article in at least one other article, the reference including a link in the at least one other article, the link providing access to the article,

a score of the at least one other article,

at least one visitation to the article by at least one user, and

a ratio of a number of occurrences of a phrase in the article to a number of words in the article;

weighting, by the host system, the increment to the score, so that more recent increments to the score have a higher weight than less recent increments; and

storing the score in association with the article in the storage system as an indication of a likelihood that users will be interested in the article.

2. The method of claim 1, wherein the article is a knowledge article and the knowledge article is an article that is on a topic that is expected to be of interest to a user.

3. The method of claim 1, further comprising:

receiving a search request from a user of the database;

ranking articles based on the score and a relevancy to the search; and

providing one or more of the articles to the user based on the ranking.

4. The method of claim 1, wherein the determining the increment for the score of the article further comprises:

determining a score based on an increment in how many references to the article are in Cases and Solutions, wherein Cases and Solutions is a record of customer complaints and solutions arrived at for customers.

5. The method of claim 1, wherein the determining the reference further comprises:

determining a score based on an increment to how many references to the article are in Questions and Answers, wherein Questions and Answers is a record of customer questions and the answers arrived at for customers.

6. The method of claim 1, wherein the votes include votes from external users, external users being users that are not internal users, internal users being users associated with an organization that runs the database system;

and votes from internal users.

7. The method of claim 6, further comprising:

weighting the votes of external users greater than the votes of internal users.

8. The method of claim 1, the score being an overall score, the method further comprising:

receiving a user-assigned score from a user; and

normalizing the user assigned score by at least changing the scale of the user assigned score from an initial scale by at least setting an average value of all possible scores of the initial scale to 0, assigning negative values to values of the initial scale that are less than the average of all scores, and assigning positive values to values of the initial scale that are greater than the average of all scores.

9. The method of claim 1, wherein the determining of the increment for the score of an article based on the detecting of the one or more visitations increases a read count of the article, and the read count of the article is stored in meta data of the article.

10. The method of claim 1, wherein the vote is stored in the article in meta data of the article.

11. The method of claim 1, wherein the score is stored in meta data of the article.

12. The method of claim 1, further comprising:

receiving at a host system, an article to store; and

storing a copy of the article in a storage accessible to the host system.

13. The method of claim 1, wherein the visitations are made by multiple users.

14. The method of claim 8, wherein user-assigned scores are received from multiple users.

15. The method of claim 1, wherein the ratio is the number of occurrences of the phrase in the article to the number of words in an abstract of the article.

16. A non-transitory machine-readable medium carrying one or more sequences of instructions, which when executed by one or more processors, cause:

determining, by a host system of a database system, the host system having a processor system including one or more processors and a storage system, an increment to a score of an article based on;

at least one vote for the article, the at least one vote being weighted higher for votes from external users than votes from internal users, the internal users being internal with respect to an organization controlling the article, the external users being external with respect to the organization,

a reference to the article in at least one other article, the reference including a link in the at least one other article, the link providing access to the article,

a score of the at least one other article,

at least one visitation to the article by at least one user, and

a ratio of a number of occurrences of a phrase in the article to a number of words in the article;

weighting, by the host system, the increment to the score, so that more recent increments to the score have a higher weight than less recent increments; and

storing the score in association with the article in the storage system as an indication of a likelihood that users will be interested in the article.

17. The non-transitory machine readable medium of claim 16, wherein the article is a knowledge article and the knowledge article is an article that is on a topic that is expected to be of interest to a user.

18. The non-transitory machine readable medium of claim 16, further comprising:

receiving a search request from a user of the database;

ranking the articles based on the final score and the relevancy to the search; and

providing one or more of the articles to the user based on the ranking.

19. A system comprising:

one or more machines having a processor system including one or more processors;

a storage system having one or more machine readable-media storing at least articles on topics that are expected to be of interest to a forum;

a relational database;

one or more machine instructions, which when invoked, cause the system to implement a method including at least;

receiving, at the system, a vote from an external user for an article;

receiving, at the processor system, a vote from an internal user;

determining an increment to a score of an article based on;

at least one vote for the article, the at least one vote being weighted higher for votes from external users than votes from internal users, the internal users being internal with respect to an organization controlling the article, the external users being external with respect to the organization,

a reference to the article in at least one other article, the reference including a link in the at least one other article, the link providing access to the article,

a score of the at least one other article,

at least one visitation to the article by at least one user, and

a ratio of a number of occurrences of a phrase in the article to a number of words in the article;

weighting, by the processor system, the increment to the score, so that more recent increments to the score have a higher weight than less recent increments; and

storing the score in association with the article in the storage system as an indication of a likelihood that users will be interested in the article.