OBJECT ORIENTED DATA AND METADATA BASED SEARCH

• US 20110231385A1
• Filed: 03/16/2010
• Published: 09/22/2011
• Est. Priority Date: 03/16/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Zhang, Hailei, Jain, Sonal, Wang, Luming, Yang, Xiaohong
• Granted Patent: US 8,473,473 B2
• Time in Patent Office: Days
• US Class Current: 707/709
• 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

An object oriented search mechanism extracts structural metadata and data based on type of document contents and data sources connected to the documents. Relationships between textual and non-textual elements within documents as well as metadata associated with the elements and data sources are utilized to generate a unified object model with the addition of semantic information derived from metadata and taxonomy, which are used to enhance search indexing, ranking of search results, and dynamic adjustment of result rendering user interface with fine tuned relevancy. Additional data from data sources connected to the documents may also be used to unlock hidden data such as data that has been filtered out in an original document.

Claims

1. A method to be executed at least in part in a computing device for performing object oriented searches, the method comprising:

crawling searched contents;

determining textual and non-textual elements within a document of the searched contents;

analyzing relationships between the elements;

analyzing metadata associated with the document and the elements; and

organizing analysis results into a unified object model for implementing indexing strategy and ranking search results by including semantic information derived from the analyzed metadata and types of elements.

2. The method of claim 1, further comprising:

determining from the metadata at least one from a set of;

a type of data associated with an element, an external data source associated with the element, and a range of available data associated with the element;

categorizing the elements according to their type; and

indicating a source of data and a type of element associated with each element in rendered search results.

3. The method of claim 2, further comprising:

deriving the semantic information and keywords from the metadata and the categorization of the metadata; and

using the semantic information and the keywords in at least one from a set of;

forming search queries, indexing, ranking and search results.

4. The method of claim 2, wherein the source of data and the type of element are indicated employing at least one of a graphical scheme and a textual scheme.

5. The method of claim 1, wherein the non-textual elements include at least one from the set of:

graphic data, an image, a video element, a chart, a diagram.

6. The method of claim 1, wherein at least one of the elements is associated with data dynamically provided from an external data source to the document.

7. The method of claim 6, further comprising:

determining additional data available from the external data source associated with the at least one of the elements; and

rendering the additional data available among the ranked search results.

8. The method of claim 1, wherein the search is performed in one of a desktop environment and a networked environment.

9. The method of claim 1, wherein the external data source includes one of:

a document and a database on one of a server, a client device, and a data store, and the method further comprises;

determining a type of the external data source; and

indicating the type of the external data source in rendered search results.

10. The method of claim 9, further comprising:

customizing crawl operations based on the types of external data sources associated with each element.

11. A computing device for facilitating object oriented searches in a networked system, the computing device comprising:

a memory;

a processor coupled to the memory, the processor executing a search engine in conjunction with instructions stored in the memory, wherein the search engine is configured to;

crawl searched contents;

determine embedded textual and non-textual elements within a document of the searched contents;

analyze relationships between the embedded elements;

analyze metadata associated with the document and the embedded elements;

organize different types of metadata and data associated with the embedded elements into generic objects employing a unified object model;

include semantic information and keywords derived from categorized metadata in the unified object model;

implement indexing strategy based on the relationships between the embedded elements and metadata represented by the generic objects;

publish indexing results from an indexing store;

rank the search results based on the relationships between the embedded elements and metadata represented by the generic objects; and

provide the ranked search results to a client application for rendering.

12. The computing device of claim 11, wherein the search engine is further configured to generate the search results by listing data available from documents, embedded elements, and external data sources associated with the documents and embedded elements.

13. The computing device of claim 11, wherein the rendered search results include an indication of result type for each search result, the result type including one of a document description, an embedded element description, and an external data source description.

14. The computing device of claim 11, wherein the search results include at least a portion of data available from an external data source associated with an embedded element but not rendered by the embedded element.

15. The computing device of claim 11, wherein the search is performed on at least one from a set of:

a database source, an analysis service, a portal, another server, and a desktop.

16. The computing device of claim 11, wherein the system comprises one of:

an enterprise-based network, a cloud-based network, and a combination of an enterprise-based network and a cloud-based network.

17. A computer-readable storage medium with instructions stored thereon for performing object oriented searches, the instructions comprising:

crawling searched contents;

determining textual and non-textual elements within a document of the searched contents;

analyzing relationships between the elements, wherein the non-textual elements include at least one from a set of;

a chart, a diagram, a video presentation, and an image;

analyzing metadata associated with the document and the elements;

organizing different types of metadata and data associated with the elements into generic objects employing a unified object model such that a scope of search results is limited to business intelligence documents, wherein the unified object model includes semantic information derived from the analyzed metadata and types of elements;

ranking the search results based on the relationships between the elements and metadata represented by the generic objects; and

rendering the search results comprising ranked documents, elements, and external data made available through the elements.

18. The computer-readable medium of claim 17, wherein the non-textual elements are embedded into the document are partially based on external data dynamically provided to the document from one of a database and another document.

19. The computer-readable medium of claim 18, wherein the instructions further comprise:

customizing a user interface of a rendering application in accordance with an indexing and ranking strategy based on the relationships between the elements and metadata represented by the generic objects such that search results representing documents, elements, and external data are displayed in a unified and consistent manner.

20. The computer-readable medium of claim 17, wherein the unified object model is part of a business intelligence abstraction layer of a business application enabling the search and rendering the search results.