Method and apparatus for correlating the results of a computer network text search with relevant multimedia files

• US 20080086453A1
• Filed: 10/05/2006
• Published: 04/10/2008
• Est. Priority Date: 10/05/2006
• Status: Abandoned Application

• Current Assignee: Fabian-Baber Incorporated
• Original Assignee: Fabian-Baber Incorporated
• Inventors: Fabian, Rhonda
• Application Number:
  US11/543,558
• Publication Number:
  US 20080086453A1
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/4393 Multimedia presentations, e.g. slide shows, multimedia albums
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

The Invention is a method and apparatus for automatic retrieval, organization, correlation and presentation of text, image, audio, or video data in a sequential manner. A user searches a database available on a computer network using a text search engine to locate a text document. The text document is automatically read and parsed to identify text portions and key phrases. The key phrases are used to automatically search a multimedia file database available on the computer network using a multimedia search engine, such as an image search engine. Multimedia documents containing multimedia files are retrieved. Text in the multimedia documents is compared to the key terms and to the query terms and the multimedia documents are ranked by relevance using a variety of techniques including ranking, indexing, statistical analysis and natural language processing. Each text portion in the text document is stored in association with the most relevant multimedia file for that text portion. The resulting correlated information is displayed to the user in a sequence of text, audio, image or video data.

Claims

1. A method for locating a text document and automatically illustrating the text document with a multimedia file using a computer network, the method comprising the steps of:

a. receiving a query term from a user;

b. conducting a search of the computer network for the text document utilizing said query term;

c. retrieving the text document from the computer network;

d. automatically parsing the text document into a plurality of key terms;

e. automatically conducting a multimedia file search on the computer network utilizing said plurality of key terms;

f. locating the multimedia file on the computer network as a result of said multimedia file search;

g. automatically associating the multimedia file and the text document;

h. communicating the text document to said user and displaying the associated multimedia file to said user contemporaneously.

2. The method of claim 1 wherein the multimedia file is a selected one of a plurality of multimedia files, said step of locating the multimedia file further comprising:

a. locating automatically said plurality of multimedia files in said multimedia file search;

b. ranking automatically each of said plurality of multimedia files by relevancy to said query term and to said one of said plurality of key terms;

c. identifying automatically a top-ranked multimedia file of said ranked plurality of multimedia files, said top-ranked multimedia file defining said selected one of said plurality of multimedia files.

3. The method of claim 2 wherein each of said plurality of multimedia files is associated within the computer database with a one of a plurality of multimedia documents, said step of ranking automatically said plurality of said multimedia files comprising:

a. ranking each of said plurality of multimedia documents for relevancy to said query term and to said one of said plurality of said key terms;

b. identifying a top-ranked multimedia document from among said plurality of multimedia documents, said top-ranked multimedia file being said one of said plurality of multimedia files associated with said top-ranked multimedia document.

4. The method of claim 3 wherein said step of automatically parsing the text document into said plurality of key terms comprises:

identifying a plurality of text portions of said text document;

parsing each of said plurality of text portions to identify a plurality of nouns, proper nouns or noun phrases, each of said plurality of said nouns, said proper nouns and said noun phrases defining a one of said plurality of key terms.

5. The method of claim 4 wherein said step of automatically associating the multimedia file and the text document and said step of communicating the text document to said user comprising:

a. connecting operably said selected multimedia file with a one of said plurality of text portions in which said key term appears;

b. displaying said one of said plurality of said text portions to said user and contemporaneously displaying said selected multimedia file to said user.

6. A method for locating a text document and automatically illustrating the text document with a multimedia file using a computer network, the method comprising the steps of:

a. receiving a query term from a user;

b. conducting a search of the computer network for the text document utilizing said query term;

c. locating the text document on the computer network;

d. automatically parsing the text document into a plurality of key terms;

e. automatically conducting a multimedia file search on the computer network utilizing a one of said plurality of key terms;

f. automatically locating a plurality of the multimedia files as a result of said multimedia file search, each of said plurality of multimedia files being associated with a one of a plurality of multimedia documents, each of said plurality of multimedia documents including a multimedia document text;

g. automatically analyzing said multimedia document text contained within each of said plurality of multimedia documents to determine a degree of relevance of each of said plurality of multimedia documents to said query term and to said one of said plurality of key terms;

h. automatically ranking each of said plurality of said multimedia documents by said degree of relevance;

i. automatically selecting a top-ranked multimedia document from said ranked plurality of said multimedia documents;

j. automatically selecting the multimedia file associated with said top-ranked multimedia document to define a selected multimedia file;

k. automatically associating said selected multimedia file and the text document;

l. communicating the text document and said selected multimedia file to said user contemporaneously.

7. The method of claim 6 wherein the text document has a text and defines a text portion, said text portion containing said one of said plurality of key terms, said step of automatically associating said selected multimedia file with the text document comprising:

operably connecting said selected multimedia file with said text portion of the text document.

8. The method of claim 7, said step of analyzing said multimedia document text contained within each of said plurality of multimedia documents comprising:

filtering said plurality of said multimedia documents and eliminating those of said plurality of multimedia documents that exhibit noise greater than a noise predetermined criterion.

9. The method of claim 8, said step of filtering said plurality of said multimedia documents comprising:

eliminating each of said plurality of said multimedia documents that does not include each said query term.

10. The method of claim 8, said step of filtering said plurality of said multimedia documents comprising:

eliminating each of said plurality of said multimedia documents in which an occurrence of a cue-phrase exceeds a cue-phrase predetermined criterion.

11. The method of claim 8, said step of filtering said plurality of said multimedia documents comprising:

eliminating each of said plurality of said multimedia documents in which an incidence of said query term or of said key phrase does not meet a query term/key phrase incidence criterion.

12. The method of claim 8, said step of analyzing said plurality of multimedia documents further comprising:

a. identifying a segment within said plurality of multimedia documents, said segment being defined by an html operator or by an emphasizing punctuation;

b. identifying a plurality of itemsets that exist within said segment of said text;

c. eliminating from said plurality of itemsets said itemsets that do not exist alone within emphasizing html appearing in said segment;

d. eliminating from said plurality of itemsets said itemsets that contain a generic word.

13. The method of claim 12, said step of analyzing said plurality of multimedia documents further comprising:

a. identifying a plurality of frequent itemsets from among said plurality of itemsets, each of said frequent itemsets having a word sequence;

b. determining a frequency of occurrence within said segment of said word sequence of each of said plurality of frequent itemsets;

c. ranking each of said plurality of frequent itemsets by said frequency of occurrence, said ranking defining a top-ranked frequent itemset based on said frequency of occurrence;

d. selecting said multimedia document in which said top-ranked frequent itemset appears, said multimedia document in which said top-ranked frequent itemset appears defining said top-ranked multimedia document.

14. The method of claim 6 wherein each of said plurality of said multimedia documents includes a plurality of a word or phrase within said multimedia document text, said step of analyzing said multimedia document text contained within each of said plurality of multimedia documents comprising:

a. reading said multimedia document text within each of said plurality of multimedia documents;

b. extracting from said multimedia document text each said word and each said phrase that exists within an emphasizing html segment.

15. The method of claim 14, said step of analyzing said multimedia document text further comprising:

a. extracting from said multimedia document text each said word and each said phrase appearing within a multimedia file description tag, said extracted words and said extracted phrases in combination defining an extracted word set for said multimedia document;

b. counting an occurrence of said query term or said key term within said extracted word set;

c. ranking each said multimedia document based on said occurrence of said query term or said key term within said extracted word set;

d. identifying a one of said multimedia documents having a greatest said occurrence of said query term or said key term within said extracted word set, said identified multimedia document defining said top-ranked multimedia document.

16. the method of claim 15, said step of ranking each said multimedia document based on said occurrence of said query term or said key term further comprising:

weighting said occurrence of said query term or said key term based upon a location of said occurrence of said query term or said key term within said multimedia document, said step of weighting said occurrence of said query term or said key term comprising providing greater weight to said query term or to said key term that appears in said multimedia document within a Meta tag segment, within a header tag segment, or in a multimedia file description tag segment.

17. The method of claim 6, said step of automatically analyzing said multimedia document text comprising:

a. counting a number of occurrences of said query term or said key term within a segment of said multimedia document, said segment being defined by a text appearing between HTML tags or said text delineated by emphasizing punctuation;

b. ranking each of said plurality of said multimedia documents based upon said counted number of occurrences of said query term or said key term within said segment of each said multimedia document.

18. The method of claim 17, said step of automatically analyzing said multimedia document text further comprising:

a. counting a number of occurrences of said query term within said multimedia document text of each of said multimedia documents;

b. summing, for each said multimedia document text, said counted number of occurrences within said segment and said counted number of occurrences of said query term within said multimedia document text to determine a total number of occurrences, said step of ranking each of said plurality of multimedia documents comprising ranking each of said plurality of multimedia documents based on said total number of occurrences of said query term within said multimedia document text and said query term or said key term in said segment.

19. The method of claim 18 wherein said segment is selected from a list consisting of said segment defined by a Meta tag and said segment defined by an emphasizing HTML.

20. The method of claim 19 wherein said total number of occurrences further comprises a number of occurrences of either said query term or said key term within an URL associated with said multimedia document.

21. The method of claim 20 wherein said URL associated with said multimedia document is selected from a list consisting of a multimedia document URL and a multimedia file URL.

22. The method of claim 6, said step of analyzing said multimedia document text further comprising:

identifying said multimedia documents that include a narrowing word.

23. The method of claim 6, said step of analyzing said multimedia document text further comprising:

identifying said multimedia documents that include a well-organized subtopic hierarchy in which said query term is included within a query term topic and said key term is included within a subtopic of said query term topic.

24. The method of claim 6, said step of analyzing said multimedia document text further comprising:

identifying multimedia documents including said query term or said key term within a pair of parenthesis symbols.

25. An apparatus for locating a text document within a computer network and illustrating the text document to a user with a multimedia file, the apparatus comprising:

a. a microprocessor, said microprocessor being configured to be connected to the computer network, said microprocessor being programmed to conduct a text search using a text search engine of a text database connected to the computer network, said microprocessor being programmed to apply a user-selected query term as a text search parameter in said text search;

b. said microprocessor being programmed to receive the text document as a result of said text search, the text document comprising a text, said microprocessor being further programmed to identify automatically a text portion of said text and to extract automatically a proper noun, a noun or a noun phrase from said text portion, said proper noun, said noun or said noun phrase defining a key term;

c. said microprocessor being programmed to conduct automatically a multimedia file search of a multimedia file database using a multimedia file search engine, said multimedia file database being available on the computer network, said microprocessor being programmed to use said key term as a multimedia file search parameter for said multimedia file search.

d. said microprocessor being programmed to receive automatically a plurality of multimedia documents as a result of said multimedia file search, each of said multimedia documents being associated with a multimedia file, each said multimedia document including an multimedia document text;

e. said microprocessor being programmed to rank automatically each said multimedia document based on a relevance of said multimedia document text included in each said multimedia document to said query term or to said key term;

f. said microprocessor being programmed to select automatically a one of said plurality of said multimedia documents based on said ranking;

g. said microprocessor being programmed to associate automatically said text portion and said multimedia file associated with said selected one of said plurality of multimedia documents;

26. The computer of claim 25 wherein said computer is programmed and configured to display said text portion of said text document and said selected multimedia file to said user simultaneously.

27. The computer of claim 26 wherein said microprocessor is programmed and configured to synthesize speech, said microprocessor being programmed to display said selected multimedia file and to read simultaneously said text document to said user using said speech synthesis.