FORM 2
The Patent Act 1970
(39 of 1970)
&
The Patent Rules  2005

COMPLETE SPECIFICATION
(SEE SECTION 10 AND RULE 13)

TITLE OF THE INVENTION
“Gaze controlled contextual web search”
APPLICANTS:
Name : HCL Technologies Limited
Nationality : Indian
Address : HCL Technologies Ltd.  50-53 Greams
Road Chennai – 600006  Tamil Nadu  India

The following Specification particularly describes and ascertains the nature of this invention and the manner in which it is to be performed:

TECHNICAL FIELD
[001] The embodiments herein relate to web searches and  more particularly  to a gaze controlled approach to automate web search.

BACKGROUND OF INVENTION
[002] Internet has established itself as a highly favored knowledge sharing media. Plenty of websites are available in the internet which provides detailed explanation on various subjects/topics. A user who is searching for details related to specific topic may perform a search in any search engine which in turn searches in associated databases and displays matching results  in any specific order as set by the user.
[003] Normally  each webpage shows information regarding multiple topics; say for example a cricket website may display information such as player profiles  team profiles  status of live matches  results of recently ended matches and so on. A user who opens that particular page may be interested in reading specific content. In the above example the user may be interested in viewing profile of a particular player. In order to view that particular player profile  the user may have to click on corresponding link  which may be a hyperlink. Similarly  the user has to manually navigate to view contents of his/her choice.
[004] Similarly  if the user has to fetch more information regarding that particular subject (i.e. the player in this example)  he/she has to continue searching using any of the available search engines. A disadvantage of these existing systems is that time consumed for manually searching for similar contents each time is more. Further  the search result accuracy may vary based on the search inputs used by the user.

SUMMARY OF THE INVENTION
[005] A method and system for automating content search on web  the method further comprises of identifying subject of interest for a user based on gaze of the user; fetching results matching the identified subject of interest from at least one associated database; and displaying the fetched results to the user.

BRIEF DESCRIPTION OF THE FIGURES
[006] The embodiments herein will be better understood from the following detailed description with reference to the drawings  in which:
[007] FIG. 1 illustrates block diagram that shows broad architecture of the gaze controlled contextual web search system  as disclosed in the embodiments herein;
[008] FIG. 2 is a block diagram that shows various components of the gaze controlled search engine and the database unit  as disclosed in the embodiments herein;
[009] FIG. 3 is a flow diagram that shows various steps involved in the process of gaze controlled contextual web search  as disclosed in the embodiments herein; and
[0010] FIG. 4 is a flow diagram that shows various steps involved in the process identifying user preference for content search  as disclosed in the embodiments herein.

DETAILED DESCRIPTION OF INVENTION
[0011] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly  the examples should not be construed as limiting the scope of the embodiments herein.
[0012] The embodiments herein disclose a contextual web search by monitoring user gaze and identifying user preference. Referring now to the drawings  and more particularly to FIGS. 1 through 4  where similar reference characters denote corresponding features consistently throughout the figures  there are shown embodiments.
[0013] FIG. 1 illustrates block diagram that shows broad architecture of the gaze controlled contextual web search system  as disclosed in the embodiments herein. The gaze controlled contextual web search system further comprises a gaze capture unit 101  a display unit 102  a gaze controlled search engine 103 and a database unit 104. The gaze capture unit 101 is preferably a camera unit that tracks user actions while he/she is browsing through a webpage. In one embodiment  the gaze controlled contextual web search system may initialize automatically when the user opens any of or a default web browser in the user device. In another embodiment  the user may have to manually initialize the gaze controlled contextual web search system. The user action may refer to head movement  gaze and/or any such actions. The data from the gaze capture unit 101 is then fed to the gaze controlled search engine 103.
[0014] The gaze controlled search engine 103 further accepts input from the display engine 102. By processing the inputs from the display unit 102 and the gaze capture unit 101  the gaze controlled search engine 102 identifies to which semantic zone (s) the user is gazing at. Further  the gaze controlled search engine 103 at least one subject of interest from a plurality of subjects in the webpage being viewed by the user. Further  the gaze controlled search engine 103 searches in the database unit 104 for all matching contents corresponding to the identified subject of interest and the results of the search are displayed to the user using the display unit 102. In various embodiments  the gaze controlled contextual web search system may be a dedicated system or may be implemented with any computing unit with inbuilt or interfaced gaze capture unit and a human readable display unit.
[0015] FIG. 2 is a block diagram that shows various components of the gaze controlled search engine and the database unit  as disclosed in the embodiments herein. The gaze controlled search engine 103 further comprises a gaze capture engine 201  a semantic engine 202  a correlation engine 203  a database resource handler 204 and a contextual processing engine 207. The database unit 104 further comprises a database engine 205 and a database 206.
[0016] The gaze capture engine 201 processes input received from the gaze capturing unit 101 and forms a gaze vector. The gaze vector may comprise information on coordinates on the device display unit 102 towards the user is gazing at  at each instance of time. The gaze vector information is further fed to the correlation engine 203.
[0017] The semantics engine 202 fetches input from the display unit 102 regarding displayed content  preferably a webpage. Further  the received information is processed and the contents being displayed on the webpage is grouped to different semantic zones. The semantic zone information is further fed to the correlation engine 203.
[0018] The correlation engine 203 processes the received semantic zone information and the gaze vector information and identifies to which semantic zone  the gaze vector is pointing at i.e. the semantic zone the user is gazing at. Once the semantic zone is identified  then the correlation engine 203 identifies the contents/subjects listed in that particular semantic zone. From the identified subjects  the correlation engine 203 identifies at least one subject of user’s interest. Further  information regarding the identified subject of interest information is fed to the database resource handler 204.
[0019] The database resource handler 204 is connected to multiple databases 206 across various enterprises and web servers in the internet through the database engine 205. The database resource handler 204 transfers information regarding the identified subject of interest to the database engine 205. The database engine 205 searches in the associated databases 206 and fetches information related to the subject of interest.
[0020] Further  the fetched information is sent to the contextual processing engine 207. The contextual processing engine 207 categorizes data received from the database engine 205 based on types of data or in any such manner specified by a user. Further  the data is sent to the display unit 102  which is then displayed to the user.
[0021] FIG. 3 is a flow diagram that shows various steps involved in the process of gaze controlled contextual web search  as disclosed in the embodiments herein. In various embodiments  the gaze controlled contextual web search system may be a dedicated system or may be implemented with any computing unit with inbuilt or interfaced gaze capture unit and a human readable display unit. When the user is browsing through a webpage  the gaze capturing unit 101 associated with the user device monitors (301) and records user action such as head movement  eye movement  eye details  and direction and towards the user is gazing at and so on.
[0022] Further  the recorded data is fed to the gaze capturing engine 201. The gaze capturing engine 201 processes the received information and forms (302) a gaze vector. The gaze capture engine 201 analyzes data such as head position  eye details and so on and measures parameters such as pixel information of eyes  distance between user head and display unit 102 and so on. The gaze capture engine 102 also fetches information regarding display dimensions of the display unit 102. By comparing the display dimensions  pixel information of the eye  distance between the user head and the display unit 102  angle at which the user is gazing at the display unit 102 and so on  the gaze capturing engine 102 identifies coordinates of the display unit 102 towards the user is gazing at  at each instance of time. This information is further embedded in the gaze vector and is then fed to the correlation engine 203.
[0023] The semantic engine 202 fetches information about content  preferably a webpage being viewed by the user at that instance of time  from the display unit 102. The semantic engine 202 then groups (303) the content being displayed on the screen/display module 102 to different semantic zones of equal size. A semantic zone may refer to a particular area of the whole screen in a specific shape; say rectangular shape. Each semantic zone may comprise information or link related to at least one subject/content. For example  when the user is browsing through a cricket related website  the webpage may display information related to various player and country profiles and statistics. Each of this player profiles and country profiles form separate subjects. The semantic engine 202 feeds the semantic zone information to the correlation engine 203.
[0024] The correlation engine 203 processes the gaze vector information and the semantic zone information and identifies to which semantic zone the gaze vector is pointing at. For example  if the gaze vector is identified to be pointing towards semantic zone “A”  then the gaze controlled contextual web search system assumes that the user is reading content/subject displayed/listed under that particular semantic zone. From the identified semantic zone  the correlation engine 203 identifies (304) at least one subject of interest for that user. Considering the above example  if user is gazing at semantic zone “A” and if the semantic zone “A” has information regarding a particular player profile  then that player/ profile is considered to be subject of interest of that user.
[0025] Further  the correlation engine 203 provides information regarding the identified subject of interest to the database resource handler 204. The database resource handler 204 passes information regarding the subject of interest to the database engine 205. The database engine 205 is connected to a plurality of databases 206 across various enterprises and web severs and searches for contents related to the identified subject of interest in the associated databases 206.
[0026] Further  the matching results obtained from the database 206 are fed to the contextual processing engine 207. The contextual processing engine may categorize the received data based on various attributes such as social media trends  social sentiments  chronological  technological and so on and sends the data to the display unit 102 and is displayed to the user. The various actions in method 300 may be performed in the order presented  in a different order or simultaneously. Further  in some embodiments  some actions listed in FIG. 3 may be omitted.
[0027] FIG. 4 is a flow diagram that shows various steps involved in the process identifying user preference for content search  as disclosed in the embodiments herein. Initially  the correlation engine 203 accepts inputs from the gaze capture engine 201 and the semantics engine 202 and processes the received inputs to identify (401) the semantic zone (s) the user is gazing at. The correlation engine 203 identifies the semantic zone to which the user is gazing at each instance of time by cross matching the gazing vector and the semantic zone information. For example  consider that the information displayed on the display unit 102 is divided into four semantic zones namely “A”  “B”  “C” and “D”. The correlation engine 203 identifies coordinates of each of the semantic zones. Further  from the gazing vector  the correlation identifies coordinate of the display unit 102 towards the user is gazing at  at that particular instance of time. The correlation engine 203 then checks whether the coordinate information present in the gazing vector matches with coordinate of any of the semantic zones. If the coordinates matches  then the correlation engine 203 assumes that the user is gazing at or is reading information in displayed in the identified semantic zone (s).
[0028] Further  the correlation engine 203 identifies the contents/subject (s) in the identified semantic zones. In an embodiment  the information regarding subjects present in each semantic zone may be provided to the correlation engine 203 by the semantic engine 202. In various other embodiments  each semantic zone may comprise one or more subjects. If the identified semantic zone (s) comprises information or link related to only one subject  then that particular subject is set (405) as the user’s subject of interest.
[0029] If the identified semantic zones comprise more than one subject  then the correlation engine 203 identifies (404) most common subject among the identified subjects. For example  consider that the user is gazing at two semantic zones namely “Zone A” and “Zone B”. The correlation engine 203 identifies that Zone A comprises information related to subjects “A”  “B” and “C”  whereas Zone B comprises information related to subjects “C” and “D”. Now  in order to identify user’s subject of interest  the correlation engine 203 checks for any common member among the identified subjects i.e. “C” in this example. So the correlation engine 203 considers “C” as the user’s subject of interest. Further  the identified common subject is set (405) as the user’s subject of interest. The various actions in method 400 may be performed in the order presented  in a different order or simultaneously. Further  in some embodiments  some actions listed in FIG. 4 may be omitted.
[0030] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements. The network elements shown in Fig. 1 include blocks which can be at least one of a hardware device  or a combination of hardware device and software module.
[0031] The embodiment disclosed herein specifies a system for automated web searches. The mechanism allows a gaze controlled web search  providing a system thereof. Therefore  it is understood that the scope of the protection is extended to such a program and in addition to a computer readable means having a message therein  such computer readable storage means contain program code means for implementation of one or more steps of the method  when the program runs on a server or mobile device or any suitable programmable device. The method is implemented in a preferred embodiment through or together with a software program written in e.g. Very high speed integrated circuit Hardware Description Language (VHDL) another programming language  or implemented by one or more VHDL or several software modules being executed on at least one hardware device. The hardware device can be any kind of device which can be programmed including e.g. any kind of computer like a server or a personal computer  or the like  or any combination thereof  e.g. one processor and two FPGAs. The device may also include means which could be e.g. hardware means like e.g. an ASIC  or a combination of hardware and software means  e.g. an ASIC and an FPGA  or at least one microprocessor and at least one memory with software modules located therein. Thus  the means are at least one hardware means and/or at least one software means. The method embodiments described herein could be implemented in pure hardware or partly in hardware and partly in software. The device may also include only software means. Alternatively  the invention may be implemented on different hardware devices  e.g. using a plurality of CPUs.
[0032] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can  by applying current knowledge  readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept  and  therefore  such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore  while the embodiments herein have been described in terms of preferred embodiments  those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the claims as described herein.

CLAIMS
We claim:
1. A method for automating content search on web  said method further comprises:
identifying subject of interest for a user based on gaze of said user;
fetching results matching said identified subject of interest from at least one associated database; and
displaying said fetched results to said user.
2. The method as in claim 1  wherein said identifying subject of interest further comprises:
grouping data displayed on a display unit of user device to a plurality of semantic zones;
identifying at least one of said plurality of semantic zones at which said user is gazing;
identifying subjects listed under said identified semantic zones; and
setting one of said identified subjects as said user’s subject of interest.
3. The method as in claim 2  wherein said identifying at least one of said plurality of semantic zones at which said user is gazing further comprises:
forming a gaze vector for said user; and
identifying at least one of said plurality of semantic zones where said gazing vector is pointing.
4. The method as in claim 3  wherein said forming said gaze vector for said user further comprises:
tracking user actions when said user is browsing through a webpage; and
identifying coordinates on said display unit at which said user is gazing.
5. The method as in claim 3  wherein said identifying at least one of said plurality of semantic zones said gazing vector is pointing  further comprises:
fetching coordinate information on said display unit towards which said user is gazing at from said gazing vector;
comparing said fetched coordinate information with coordinate information of each of said plurality of semantic zones; and
identifying at least one semantic zone whose coordinate information matches with said fetched coordinate information from said gazing vector.
6. The method as in claim 2  wherein said setting one of said identified subjects as subject of interest for said user further comprises:
identifying if number of subjects listed under said identified semantic zones is more than one;
setting said listed subject as user’s subject of interest  if number of subjects listed under said identified semantic zones not more than one;
identifying most common subject among said listed subjects  if number of subjects listed under said identified semantic zones is more than one; and
setting said identified most common subject as said subject of interest for said user.
7. A system for automating content search on web  said system is further configured for
identifying subject of interest for a user based on gaze of said user;
fetching results matching said identified subject of interest from at least one associated database; and
displaying said fetched results to said user.
8. The system as in claim 7  wherein said system is configured for identifying subject of interest by:
grouping data displayed on a display unit of user device to a plurality of semantic zones;
identifying at least one of said plurality of semantic zones at which said user is gazing;
identifying subjects listed under said identified semantic zones; and
setting one of said identified subjects as said user’s subject of interest.
9. The system as in claim 8  wherein said system is configured for identifying at least one of said plurality of semantic zones at which said user is gazing further comprises by:
forming a gaze vector for said user; and
identifying at least one of said plurality of semantic zones where said gazing vector is pointing.
10. The system as in claim 9  wherein said forming said gaze vector for said user further comprises:
tracking user actions when said user is browsing through a webpage; and
identifying coordinates on said display unit at which said user is gazing.
11. The system as in claim 10  wherein said system is configured for identifying at least one of said plurality of semantic zones said gazing vector is pointing by:
fetching coordinate information on said display unit towards which said user is gazing at from said gazing vector;
comparing said fetched coordinate information with coordinate information of each of said plurality of semantic zones; and
identifying at least one semantic zone whose coordinate information matches with said fetched coordinate information from said gazing vector.
12. The system as in claim 8  wherein said system is configured for setting one of said identified subjects as subject of interest for said user by:
identifying if number of subjects listed under said identified semantic zones is more than one;
setting said listed subject as user’s subject of interest  if number of subjects listed under said identified semantic zones not more than one;
identifying most common subject among said listed subjects  if number of subjects listed under said identified semantic zones is more than one; and
setting said identified most common subject as said subject of interest for said user.
Dated: 5th Day of December 2012 Signature:

Dr Kalyan Chakravarthy
(Patent Agent)

ABSTRACT
The embodiments herein relate to web searches and  more particularly  to a gaze controlled approach to automate web search. The system identifies coordinates of the display unit the user is gazing at  at each instance of time and forms corresponding gaze vectors. Further  data displayed on the display unit is grouped into different semantic zones; with each semantic zone having different coordinates. By comparing coordinate information in the gaze vector and each of the semantic zones  the system identifies semantic zone the user is gazing at. Further  from the identified semantic zones  the system identifies a subject of interest for that user. A search is performed in the associated databases with the subject of interest as the key and the results are displayed to the user.
FIG. 1