TENANTIZATION OF SEARCH RESULT RANKING

• US 20130110828A1
• Filed: 11/02/2011
• Published: 05/02/2013
• Est. Priority Date: 11/02/2011
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Meyerzon, Dmitriy, Petriuc, Mihai, Bodd, Nicolai
• Granted Patent: US 8,694,507 B2
• Time in Patent Office: Days
• US Class Current: 707/728
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results

Abstract

This disclosure describes methods and systems for searching documents in a multi-tenant hosting environment. According to embodiments, to conserve hardware resources, a plurality of documents associated with a plurality of tenants may be mapped to the same search index in the multi-tenant hosting environment. In order to search documents associated only with a single tenant in the multi-tenant hosting environment, a tenant identifier is prepended to every key stored in the search index that is associated with the plurality of documents of the single tenant. Moreover, where one document links to another document within the multi-tenant hosting environment, the link is stored in a web graph when a source tenant identifier matches a target tenant identifier for the link. According to embodiments, when conducting a search, the link is resolved only if the link is stored in the web graph.

Claims

1. A computer storage medium storing computer-executable instructions for implementing a method of indexing a first document in a multi-tenant hosting environment, the method comprising:

indexing a first property of a first document in a search index, comprising;

identifying a first plurality of keys in the first property of the first document;

prepending a first tenant identifier to each key of the first plurality of keys to form a first plurality of first tenant identifier-key combinations;

storing the first plurality of first tenant identifier-key combinations in a search index; and

mapping the first property of the first document to each of the first plurality of first tenant identifier-key combinations in the search index.

2. The computer storage medium of claim 1, further comprising indexing a second property of the first document in the search index, comprising:

identifying a second plurality of keys in the second property of the first document, wherein the second plurality of keys has one or more keys in common with the first plurality of keys;

prepending the first tenant identifier to each key of the second plurality of keys to form a second plurality of first tenant identifier-key combinations, wherein the second plurality of first tenant identifier-key combinations has one or more first tenant identifier-key combinations in common with the first plurality of first tenant identifier-key combinations; and

mapping the second property of the first document to each of the second plurality of first tenant identifier-key combinations in the search index.

3. The computer storage medium of claim 1, further comprising:

identifying a length of the first property of the first document; and

storing the length of the first property.

4. The computer storage medium of claim 3, further comprising:

retrieving the length of the first property in each document of a plurality of documents associated with a first tenant of the multi-tenant hosting environment;

calculating an average document length for the first property associated with the first tenant; and

storing the average document length for the first property associated with the first tenant.

5. The computer storage medium of claim 1, further comprising:

determining a document frequency for each first tenant identifier-key combination; and

storing the document frequency for each first tenant identifier-key combination.

6. The computer storage medium of claim 1, further comprising:

detecting a link in the first document that references a second document;

detecting a source tenant identifier associated with the first document; and

detecting a target tenant identifier associated with the second document.

7. The computer storage medium of claim 6, further comprising:

storing the link in a web graph when the target tenant identifier matches the source tenant identifier.

8. The computer storage medium of claim 6, further comprising:

not storing the link in a web graph when the target tenant identifier does not match the source tenant identifier.

9. A computer system, comprising:

at least one processor; and

at least one memory, communicatively coupled to the at least one processor and containing computer-readable instructions that, when executed by the at least one processor, perform a method of searching a plurality of documents associated with a tenant in a multi-tenant hosting environment, the method comprising;

receiving a search key from a tenant in a multi-tenant hosting environment, wherein the search key is prepended to a tenant identifier associated with the tenant to form a tenant identifier-search key combination;

querying a search index for a tenant identifier-key combination that corresponds with the tenant identifier-search key combination; and

returning one or more documents mapped to the corresponding tenant identifier-key combination, wherein the one or more documents are associated with the tenant in a multi-tenant hosting environment.

10. The computer system of claim 9, further comprising:

identifying a first document of the one or more documents;

retrieving an average document length for each property of the first document that is mapped to the corresponding tenant identifier-key combination;

retrieving a total document count associated with the tenant;

retrieving a document frequency for the corresponding tenant identifier-key combination; and

calculating a predicted relevance for the first document.

11. The computer system of claim 10, further comprising:

identifying a second document of the one or more documents;

retrieving an average document length for each property of the second document mapped to the corresponding tenant identifier-key combination;

retrieving the total document count associated with the tenant;

retrieving the document frequency for the corresponding tenant identifier-key combination; and

calculating a predicted relevance for the second document.

12. The computer system of claim 11, further comprising:

ranking the first document and the second document in order of decreasing predicted relevance.

13. The computer system of claim 10, further comprising:

detecting a first link referencing the first document, wherein the first link is in a second document;

accessing a web graph, wherein the web graph stores the first link only when a source tenant identifier for the second document matches a target tenant identifier for the first document;

resolving the first link only when the first link is stored in the web graph; and

upon resolving the first link, calculating the predicted relevance for the first document based at least in part upon an anchor text property in the second document.

14. The computer system of claim 11, further comprising:

detecting a second link referencing the second document, wherein the second link is in a third document;

accessing a web graph, wherein the web graph stores the second link only when a source tenant identifier for the third document matches a target tenant identifier for the second document;

resolving the second link only when the second link is stored in the web graph; and

upon resolving the link, calculating the predicted relevance for the second document based at least in part upon an anchor text property in the third document.

15. The computer system of claim 14, further comprising:

ranking the first document and the second document in order of decreasing predicted relevance.

16. The computer system of claim 15, further comprising displaying at least a subset of the one or more documents in order of decreasing predicted relevance.

17. A computer-implemented method of searching a plurality of documents associated with a tenant in a multi-tenant hosting environment, the method comprising:

receiving a search key from a tenant in a multi-tenant hosting environment, wherein the search key is prepended to a tenant identifier associated with the tenant to form a tenant identifier-search key combination;

querying a search index for a tenant identifier-key combination that corresponds with the tenant identifier-search key combination; and

returning one or more documents mapped to the corresponding tenant identifier-key combination, wherein the one or more documents are associated with the tenant in a multi-tenant hosting environment.

18. The computer-implemented method of claim 17, further comprising:

identifying a first document of the one or more documents;

detecting a link in the first document, wherein the link references a second document;

accessing a web graph, wherein the web graph stores the link only when a source tenant identifier matches a target tenant identifier associated with the link; and

resolving the link only when the link is stored in the web graph.

19. The computer-implemented method of claim 18, further comprising:

retrieving an average document length for each property of the first document mapped to the corresponding tenant identifier-key combination;

retrieving a total document count associated with the first tenant;

retrieving a document frequency for the corresponding tenant identifier-key combination; and

calculating a predicted relevance for the first document.

20. The computer-implemented method of claim 19, wherein upon resolving the link, the method further comprises:

calculating the predicted relevance for the first document based at least in part upon an anchor text property in the second document.