SYSTEM FOR DISCOVERING DATA ARTIFACTS IN AN ON-LINE DATA OBJECT

• US 20080147642A1
• Filed: 03/08/2007
• Published: 06/19/2008
• Est. Priority Date: 12/14/2006
• Status: Abandoned Application

• Current Assignee: ProQuo, Inc.
• Original Assignee: ProQuo, Inc.
• Inventors: Yakyma, Oleksandr, Leffingwell, Dean, Korolev, Aleksey, Widrig, Donald R., Miller, Jeremie
• Application Number:
  US11/683,941
• Publication Number:
  US 20080147642A1
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9538 Presentation of query results

Abstract

A system for discovering data artifacts in an on-line data object is described. One embodiment includes a data acquisition subsystem configured to parse the on-line data object into at least one string; a string pre-parser configured to divide each string into a set of separate characters; a lexical analyzer configured, for each set of separate characters, to aggregate the separate characters in that set of separate characters into a sequence of tokens, each token in the sequence of tokens being one of a word, a punctuation symbol, a HyperText-Markup-Language tag, and a number; a syntax analyzer configured, for each sequence of tokens during a first analysis phase, to determine, for each of a plurality of rule sets, whether the sequence of tokens includes one or more candidate data artifacts of a distinct type to which that rule set corresponds, each of the plurality of rule sets being adapted to discovery of the distinct type of data artifact to which that rule set corresponds, at least one rule set in the plurality of rule sets including a context-free grammar; compute, for each candidate data artifact of a distinct type, a probability ranking indicating a degree of likelihood that the candidate data artifact is a data artifact of that distinct type; and classify each candidate data artifact as a data artifact of the distinct type for which a most favorable probability ranking was computed for that candidate data artifact, the syntax analyzer being configured to associate with each classified data artifact a subject found within the on-line data object; and a storage subsystem including at least one data structure in which to store the classified data artifacts, the storage subsystem being configured to index and organize the classified data artifacts by subject for retrieval in response to a search query indicating a particular subject.

Claims

1. A system for discovering data artifacts in an on-line data object, the system comprising:

a data acquisition subsystem configured to parse the on-line data object into at least one string;

a string pre-parser configured to divide each string into a set of separate characters;

a lexical analyzer configured, for each set of separate characters, to aggregate the separate characters in that set of separate characters into a sequence of tokens, each token in the sequence of tokens being one of a word, a punctuation symbol, a HyperText-Markup-Language tag, and a number;

a syntax analyzer configured, for each sequence of tokens during a first analysis phase, to;

determine, for each of a plurality of rule sets, whether the sequence of tokens includes one or more candidate data artifacts of a distinct type to which that rule set corresponds, each of the plurality of rule sets being adapted to discovery of the distinct type of data artifact to which that rule set corresponds, at least one rule set in the plurality of rule sets including a context-free grammar;

compute, for each candidate data artifact of a distinct type, a probability ranking indicating a degree of likelihood that the candidate data artifact is a data artifact of that distinct type; and

classify each candidate data artifact as a data artifact of the distinct type for which a most favorable probability ranking was computed for that candidate data artifact;

the syntax analyzer being configured to associate with each classified data artifact a subject found within the on-line data object; and

a storage subsystem including at least one data structure in which to store the classified data artifacts, the storage subsystem being configured to index and organize the classified data artifacts by subject for retrieval in response to a search query indicating a particular subject.

2. The system of claim 1, wherein the on-line data object is a Web page.

3. The system of claim 2, wherein the system is configured to process a collection of Web pages encompassing substantially all of the World Wide Web.

4. The system of claim 2, wherein the data acquisition subsystem is configured to remove duplicate Web pages from the collection of Web pages.

5. The system of claim 1, wherein the on-line data object is one of a Usenet news posting, an e-mail message, and a Web feed

6. The system of claim 1, wherein a subject is a name of a person.

7. The system of claim 1, wherein the syntax analyzer is configured, for a given distinct type of data artifact, to:

match one or more tokens in the sequence of tokens with at least one of a set of predetermined patterns defined by the context-free grammar of the rule set that corresponds to the given distinct type of data artifact, wherein, in matching one or more tokens in the sequence of tokens with at least one of a set of predetermined patterns defined by the context-free grammar of the rule set that corresponds to the given distinct type of data artifact, the syntax analyzer is configured to compare at least one token among the one or more tokens with a database of known data values.

8. The system of claim 7, wherein the given distinct type of data artifact is a name of a person and the database of known values is a database of known name parts, the database of known name parts including at least one of first names, last names, name prefixes, and name suffixes.

9. The system of claim 8, wherein the syntax analyzer is configured to:

identify at least one morphological variation of a candidate name-part token before the candidate name-part token is compared with a database of known name parts including first names; and

compare each of the at least one morphological variations with the database of known name parts including first names.

10. The system of claim 8, wherein the syntax analyzer is configured to recognize a group of tokens as a candidate name of a person when the group of tokens includes a combination of a candidate name-part token that is found in the database of known name parts and a candidate name-part token that is not found in the database of known name parts.

11. The system of claim 7, wherein the given distinct type of data artifact is a geographic location and the database of known values is a database of known geographic locations, the database of known geographic locations including at least one of countries, U.S. states, partial names of U.S. states, provinces, cities, partial names of cities, and place names.

12. The system of claim 11, wherein data artifacts classified as a geographic location are hierarchically distinguished by their respective geographic scopes in the storage subsystem to enable search results retrieved from the storage subsystem to be limited in accordance with a geographic scope specified by a user.

13. The system of claim 7, wherein the given distinct type of data artifact is a name of an organization and the database of known values is a database of known organization names, the database of known organization names including at least one of organization root names and organization suffixes.

14. The system of claim 13, wherein the syntax analyzer is configured to infer an affiliation between a name of a person and a data artifact classified as a name of an organization based at least in part on proximity, within the on-line data object, of the data artifact classified as a name of an organization to the name of the person.

15. The system of claim 1, wherein the syntax analyzer is configured, for each sequence of tokens during a second analysis phase subsequent to the first analysis phase, to:

apply to the sequence of tokens a tags rule set distinct from the plurality of rule sets, the tags rule set corresponding to a tag data-artifact type, the tags rule set being adapted to discovery of the tag data-artifact type, the tags rule set including a context-free grammar;

match one or more tokens in the sequence of tokens with at least one of a set of characteristic tag patterns defined by the context-free grammar, the one or more tokens not having been classified as a data artifact during the first analysis phase, wherein, in matching one or more tokens in the sequence of tokens with at least one of a set of characteristic tag patterns defined by the context-free grammar, the syntax analyzer is configured to compare a token among the one or more tokens with a database of tag terms, the database of tag terms including at least one of nouns, pronouns, prepositions, conjunctions, articles, and auxiliary verbs; and

when the tags rule set is satisfied;

classify the one or more tokens as a tag data artifact; and

associate the tag data artifact with a subject found within the on-line data object.

16. The system of claim 15, wherein the syntax analyzer is configured, when the tags rule set is satisfied, to determine a key-token density of the one or more tokens and to classify the one or more tokens as a tag data artifact when the key-token density satisfies a predetermined key-token-density criterion.

17. The system of claim 15, wherein the tag data artifact represents miscellaneous information about the subject associated with the tag data artifact.

18. The system of claim 1, wherein the syntax analyzer is configured, for each sequence of tokens during an analysis phase subsequent to the first analysis phase, to:

apply to the sequence of tokens a text-block rule set distinct from the plurality of rule sets, the text-block rule set corresponding to a text-block data-artifact type, the text-block rule set being adapted to discovery of the text-block data-artifact type, the text-block rule set including a context-free grammar;

match at least a portion of the sequence of tokens with at least one of a set of characteristic text-block patterns defined by the context-free grammar; and

when the text-block rule set is satisfied;

classify as a text-block data artifact the at least a portion of the sequence of tokens; and

associate the text-block data artifact with a subject found within the on-line data object.

19. The system of claim 18, wherein the text-block data-artifact type is one of a clipping, an item concerning education, and a biography.

20. The system of claim 18, wherein the text-block data artifact contains within it at least one previously discovered data artifact.

21. The system of claim 1, wherein the distinct types of data artifacts include at least one of an identifier associated with a manner of electronically communicating with a person, a hobby, an interest, and an image, each image data artifact having a corresponding image reference, the image reference corresponding to each image data artifact being stored in the storage subsystem.

22. The system of claim 1, wherein the string pre-parser is configured to convert each set of separate characters to a canonical form in a predetermined target language.

23. The system of claim 1, wherein the storage subsystem includes a fast index and an artifact dictionary, the classified data artifacts being stored non-redundantly in the artifact dictionary, the fast index containing pointers to the artifact dictionary, the pointers being organized by subject.

24. The system of claim 23, wherein at least one of the fast index and the artifact dictionary is distributed over a plurality of servers.

25. The system of claim 1, wherein data artifacts of a given distinct type and portions thereof are hierarchically distinguished by their respective scopes in the storage subsystem to enable search results retrieved from the storage subsystem to be limited in accordance with a scope specified by a user.