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(12) United States Patent (10) Patent No.: US 7.546,280 B1 Ershov (45) Date of Patent: *Jun

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(12) United States Patent (10) Patent No.: US 7.546,280 B1 Ershov (45) Date of Patent: *Jun USOO754628OB1 (12) United States Patent (10) Patent No.: US 7.546,280 B1 Ershov (45) Date of Patent: *Jun. 9, 2009 (54) USE OF NEURAL NETWORKS FOR 5,819,245 A * 10/1998 Peterson et al. ............... TO6, 16 KEYWORD GENERATION 6,304.864 B1* 10/2001 Liddy et al. ................... TO6.15 (75) Inventor: Alexander V. Ershov, Sergiev Posad (RU) (Continued) OTHER PUBLICATIONS (73) Assignee: Quintura, Inc., Alexandria, VA (US) "Inhibitory connections in the assembly neural network for texture (*) Notice: Subject to any disclaimer, the term of this segmentation'. A. Goltsev, Donald C. Wunsch, Neural Networks, patent is extended or adjusteds under 35 WO 1. 11, No.O. 5, Jul. 1998, pppp. 951-962.* U.S.C. 154(b) by 379 days. (Continued) is- Primary Examiner David R Vincent This patent is Subject to a terminal dis Assistant Examiner Mai T Tran Ca10. (74) Attorney, Agent, or Firm Bardmesser Law Group (22) Filed: Sep. 27, 2006 A system for identifying keywords in search results includes Related U.S. Application Data a plurality of neurons connected as a neural network, the (63) Continuation-in-part of application No. 1 1/468,692. neurons being associated with words and documents . An activity regulator regulates a minimum and/or maximum filed on Aug. 30, 2005, now Pat. No. 7,475,072. number of neurons of the neural network that are excited at (60) Provisional application No. 60/735,858, filed on Nov. any given time. Means for displaying the neurons to a user 14, 2005, provisional application No. 60/722,412, and identifying the neurons that correspond to keywords can filed on Oct. 3, 2005, provisional application No. be provided. Means for changing positions of the neurons 60/719,975, filed on Sep. 26, 2005. relative to each other based on input from the user can be s- a-s s provided. The change in position of one neuron changes the (51) Int. Cl. keywords. The input from the user can be dragging a neuron G06E I/00 (2006.01) on a display device, or changing a relevance of two neurons 52) U.S. C 706/20: 707/6 relative to each other. The neural network can be excited by a (52) ir grgrrr. s query that comprises words selected by a user. The neural (58) Field of Classification Search ................... 706/20; network can be abidirectional network. The user can inhibit 707/6 neurons of the neural network by indicating irrelevance of a See application file for complete search history. document. The neural network can be excited by a query that (56) References Cited identifies a document considered relevant by a user. The neu ral network can also include neurons that represent groups of U.S. PATENT DOCUMENTS words. The neural network can be excited by a query that identifies a plurality of documents considered relevant by a 5,086.479 A * 2/1992 Takenaga et al. ............ 382,157 user, and can output keywords associated with the plurality of 5.535,303 A * 7/1996 Ekchian et al. ............... T06/26 documents. 5,546,503 A * 8/1996 Abe et al. ..................... 7O6.25 5,548,683 A * 8/1996 Engel et al. ................... T06/20 24 Claims, 5 Drawing Sheets INACTIVENEURON - XCITEDNEURON m INHIBITING NEURON ... MAGNIFYING CONNECTION ... INHIBITING CONNECTION C C M K EY O US 7.546,280 B1 Page 2 U.S. PATENT DOCUMENTS OTHER PUBLICATIONS 6,463,423 B1 * 10/2002 Wada .......................... TO6.15 "Structure of Neural Assembly” by E. M. Kussul, T. N. Baidyk, 6,574,632 B2 * 6/2003 Fox et al. .................... 707/102 Neuroinformatics and Neurocomputers, 1992, RNNS/IEEE Sympo 7,296,009 B1 * 1 1/2007 Jiang et al. ..................... 707/3 sium on, s M.A. Sir 423-434. 1 ck “An assembly neural network for texture segmentation'. A. Goltsev 2003/02169 19 A1* 11/2003 Roushar ..................... TO4,260 Neural Networks, vol. 9, No. 4, Jun. 1996, pp. 643-653.* 2005/024.6296 A1* 11/2005 Ma et al. ...................... TO6/12 2007/0009151 A1 1/2007 Pittman et al. .............. 382,159 * cited by examiner U.S. Patent Jun. 9, 2009 Sheet 1 of 5 US 7.546,280 B1 O - INACTIVE NEURON (D - EXCITED NEURON () - INHIBITING NEURON -s ...... MAGNIFYING CONNECTION w ...... INHIBITING CONNECTION yY WORDS OBJECTS SENTENCES DOCUMENTS : i APPLE & u-- - - o Ys - C&N I-C)FRUIT ( -" Q-N S.ra sea-------A------J. us &\\ is y M. i arr rra combuTER)-\\- //O- Kirst Sis-Avi Su's v Y, 's-ck Y y Y.\ S- v --- -1 n . N k \- N l Y y w KEYBOARD O^^g. HARDWARE DO--- s y v. \\ O Y i- I \ l \ Y- v \ --- ^ X --Y. 1 -ol. \ ar. \ & N Ex ser sy - | ADAM re-Y N O - \-ANATOMY i - N res.~~ - \ M i S. O. o- or i sr S. Y. k LOUID CIDER i. 1- Y'^^ ' Y- \-- ...r FIG. 1 U.S. Patent Jun. 9, 2009 Sheet 2 of 5 US 7.546,280 B1 O U.S. Patent Jun. 9, 2009 Sheet 3 of 5 US 7.546,280 B1 U.S. Patent Jun. 9, 2009 Sheet 4 of 5 US 7.546,280 B1 U.S. Patent Jun. 9, 2009 Sheet 5 of 5 US 7.546,280 B1 PrOCeSSOr 301 302 FIG. 3 Main Memory 308 Secondary Memory 310 Hard Disk Drive 312 Removable Storage Removable Drive 314 Storage Unit 318 Removable Interface 320 Storage Unit 422 NetWOrk Interface 323 COmmunicationS Path 326 US 7,546,280 B1 1. 2 USE OF NEURAL NETWORKS FOR and managing the search process. Keywords identify what the KEYWORD GENERATION documents are “about they may be words that are men tioned in the documents themselves, or they may be concepts CROSS-REFERENCE TO RELATED that are related to the meaning of the document, and which APPLICATIONS capture, in one or a handful of words, the meaning of the document. Accordingly, there is a need in the art for an effec This application is a continuation-in-part of U.S. patent tive and efficient system and method for identifying keywords application Ser. No. 1 1/468,692, filed on Aug. 30, 2006, relating to context-based searching. entitled CONTEXT-BASED SEARCH VISUALIZATION AND CONTEXT MANAGEMENT USING NEURAL 10 SUMMARY OF THE INVENTION NETWORKS, which is a non-provisional of U.S. Provisional Patent Application No. 60/719,975, filed on Sep. 26, 2005, Accordingly, the present invention is related to use of neu entitled CONTEXT-BASED SEARCH VISUALIZATION ral networks for keyword generation that substantially obvi USING NEURAL NETWORKS, and is a non-provisional of ates one or more of the disadvantages of the related art. U.S. Provisional Patent Application No. 60/735,858, filed on 15 In one aspect, there is provided a system for identifying Nov. 14, 2005, entitled ONE-CLICK SEARCHING SYS keywords in search results including a plurality of neurons TEMAND METHOD, which are both incorporated by ref connected as a neural network, the neurons being associated erence herein in their entirety. with words and documents. An activity regulator regulates a This application is a non-provisional of U.S. Provisional minimum and/or maximum number of neurons of the neural Patent Application No. 60/722,412, filed on Oct. 3, 2005, network that are excited at any given time. Means for display entitled USE OF NEURAL NETWORKS FOR KEYWORD ing the neurons to a user and identifying the neurons that GENERATION, which is incorporated by reference herein in correspond to keywords can be provided. Means for changing their entirety. positions of the neurons relative to each other based on input from the user can be provided. The change in position of one BACKGROUND OF THE INVENTION 25 neuron changes the keywords. The input from the user can be dragging a neuron on a display device, or changing a rel 1. Field of the Invention evance of two neurons relative to each other. The neural The present invention relates to generation of keywords for network can be excited by a query that comprises words document digesting, and, more particularly, to keyword gen selected by a user. The neural network can be abidirectional eration for search engine output as a means for assisting the 30 network. The user can inhibit neurons of the neural network user in selecting relevant documents and search results. by indicating irrelevance of a document. The neural network 2. Description of the Related Art can be excited by a query that identifies a document consid The World Wide Web (“web”) contains a vast amount of ered relevant by a user. The neural network can also include information. Locating a desired portion of the information, neurons that represent groups of words. The neural network however, can be challenging. This problem is compounded 35 because the amount of information on the web and the num can be excited by a query that identifies a plurality of docu ber of new users inexperienced at web searching are growing ments considered relevant by a user, and can output keywords rapidly. associated with the plurality of documents. In another aspect, a system, method and computer program Search engines attempt to return hyperlinks to web pages product for identifying keywords, include a plurality of neu in which a user is interested. Generally, search engines base 40 their determination of the users interest on search terms rons arranged into a neural network comprising a plurality of (called a search query) entered by the user. The goal of the layers, the layers including words, objects and documents. A search engine is to provide links to high quality, relevant plurality of connections connect the neurons, such that each neuron is connected to only some of the other neurons.
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