Searches over a collection of items through classification and display of media galleries

Architecture is provided for performing multimedia searches and returning media galleries, and then prominently displaying the galleries to a user. The disclosed innovation generates a gallery classifier and then displays found galleries to the user in a new and informative user interface. In one aspect, a system is provided that facilitates searching data for gallery pages. The system includes a gallery classifier that receives web data associated with web pages, and identifies a web page as a gallery page during a search operation. The system also includes a gallery user interface that presents a gallery page and associated content as part of the search process.

BACKGROUND

With the advent of the Internet, enormous amounts of information have been made accessible via the network to users of all skill levels and backgrounds. This also applies to technological advances in hardware storage systems that facilitate storing large amounts of data (e.g., gigabytes and terabytes) on a user's home computer. Users, both home and professional, are now prone to store anything and everything since the cost to do so is becoming cheaper. Advances in network bandwidth as well as computing bandwidth have facilitates the generation and transmission of all kinds and types of content. In the not too recent past, the content that dominated the Internet was primarily text-based content. However, multimedia content (e.g., audio, video and image content) provides a more rich experience can now be considered dominate all web site content and will be communicated easily to millions of users, thereby making data organization and searching even more difficult. Multimedia content is being provided for access via most any device and system, including fixed and portable computers, cellular telephones, and IP-connected televisions, for example.

Today, multimedia search engines, and image search engines in particular, provide poor user experiences. When a user searches for an image, they are oftentimes trying to find multiple good images and then trying to browse those images. This implies that image search providers should aim to provide a faster route to pages that offer a gallery-like user experience. Moreover, users expect similar browse-oriented behaviors in audio and video searches.

Currently, no search engine properly addresses this problem because none of them place value in the concept of an image or a media gallery (a page dedicated to browsing media).

SUMMARY

Disclosed herein is an improved architecture for performing multimedia searches. The invention identifies image or media galleries and then prominently displays the galleries to a user. By returning the more useful, browse-friendly results to the user, the overall user experience is improved.

The disclosed innovation generates a gallery classifier and then displays found galleries to the user in a new and informative user interface. A specific example is the following. If a user is interested in space travel and searches for photos of a NASA space launch, the user wants to see what it looks like when a shuttle takes off and various other related images to learn more. The user can navigate to an image search and type in a query such as “NASA space launch”. In conventional systems, the user would receive a screen of thumbnail images most of which point to a web page of mostly text and 1-2 images, some of which include hyperlinks that point to web pages with many images of the NASA space launch. In accordance with this innovation, the web pages with many useful pictures will be bubbled up to the top of the results so that the user is directed towards the more useful browser-oriented pages.

The invention disclosed and claimed herein, in one aspect thereof, comprises a system that facilitates searching web pages for gallery pages or media galleries. The system can include a classification component that receives web data associated with web pages, and generates a likelihood values that a web page is a gallery page during a search operation. The system can also include a presentation component that facilitates presentation of a gallery page as part of the search operation.

In another aspect of the subject invention, a gallery page user interface is provided for presenting audio, video, and/or image content.

In yet another aspect thereof, a machine learning and reasoning component is provided that employs a probabilistic and/or statistical-based analysis to prognose or infer an action that a user desires to be automatically performed.

DETAILED DESCRIPTION

While certain ways of displaying information to users are shown and described with respect to certain figures as screenshots, those skilled in the relevant art will recognize that various other alternatives can be employed. The terms “screen,” “web page,” and “page” are generally used interchangeably herein. The pages or screens are stored and/or transmitted as display descriptions, as graphical user interfaces, or by other methods of depicting information on a screen (whether personal computer, PDA, mobile telephone, or other suitable device, for example) where the layout and information or content to be displayed on the page is stored in memory, database, or another storage facility.

Described herein is an improved system for performing multimedia content searches. This invention improves upon the prior art by providing architecture for identifying media galleries and then prominently displaying them to a user. By returning these more useful, browse-friendly results to the user, the overall user experience is improved. One benefit allows the end user to get to the final desired experience of browsing relevant multimedia content faster.

Referring initially to the drawings,FIG. 1illustrates a system100that facilitates searching data gallery page processing in accordance with an innovative aspect. The system100can include a classification component102that receives web data associated with web pages, and can identify a web page as a gallery page during a search operation based on the web page data. The system100can also include a presentation component104that presents a gallery page via a user interface as part of the search results.

At200, a search for multimedia content is initiated. This can be a search conducted over the Internet, a LAN, WAN, or any network that provides access to gallery data. At202, web pages are returned as search results. The web pages are passed into parser to parse the web page data and content into a web page structure which can be further processed. At204, the page structure data is passed to a gallery classifier that analyzes the structure data against predetermined criteria. At206, the system checks if the web page is a gallery page. If so, at208, the web page is stored and/or presented in the search results as a gallery page. If the web page is determined not to include gallery data, flow is from206to210to either discard the web page or save and present as a non-gallery web page. Flow then proceeds back to200to process the next search and associated web pages.

Referring now toFIG. 3, there is illustrated a methodology of presenting a gallery page in accordance with another aspect. At300, a query is submitted for a multimedia search. At302, multimedia results are returned and processed. At304, gallery pages are separated from other search results. At306, the gallery pages are presented based on the query.

FIG. 4illustrates a more detailed schematic block diagram of a system400that facilitates gallery searching processing according to an aspect. A network402of one or more web sites404having one or more web pages that are accessible during a search operation. A web crawler406receives and processes a query against the network of web sites404, as shown at408. The web crawler406feeds documents to a parser410to parse page data for structure. In this implementation, the parser410includes a gallery classifier412as well as other classifiers414that function to detect other types of content.

The media gallery classifier412is used to identify galleries when web pages are being parsed. A classifier, when employed in a search engine, is an added component used to identify certain types of pages. For example, in searches today, other classifiers such as a spam classifier and an adult content classifier can be provided to identify pages that are considered spam. This innovation expands the classifier functionality to also include the gallery classifier412to identify gallery pages. A gallery is a page that focuses on the media it contains (e.g., image, video, audio), is used mainly for browsing, and has a user experience centered on the media itself. The gallery classifier412is included into the crawler/parser/builder pipeline processes of a search to process structure data after the parsing is complete. Once the structure of the page is known from the parser410, that information is fed into the gallery classifier412to make an informed guess at to whether or not a page is a gallery page.

A criteria component416interfaces to the gallery classifier412to allow access to predetermined criteria stored therein. For example, the predetermined criteria can include analyzing the number of media items on a page, the location of the media on a page, the page layout, the amount of text per media item, and the media file type, and the number files with similar file name text, for example. Thus, once the page structure is obtained, the structure data can be processed by the gallery classifier412using the criteria of the criteria component416.

Classification is based on the determined page characteristics. For example, a web page that might be considered a gallery could have over thirty images of all the same size and located in an HTML (hypertext markup language) table. Alternatively, a gallery may be a DHTML (dynamic HTML) web page that contains many similarly-sized image thumbnails which expand to full images when the user hovers a pointing device cursor over a thumbnail image. Likewise, a video gallery page could be a page with many video links, all with similar formatting and description length. An audio gallery could be a list of audio files with similar formats and all with some associated text. Characteristics that are found to be common to galleries will then be included in the criteria component416as part of the gallery classifier system412.

When the gallery classifier412determines that there is a high likelihood that the page is a gallery page, this information is passed from the parser to an index builder418which builds an index of the gallery pages. The index of gallery information can be ranked and/or gallery data pulled from the index builder418can be ranked using a ranking component420prior to representation via a gallery interface422, which presents gallery page information to a user.

FIG. 5illustrates an alternative implementation of a server-based gallery search system500according to an aspect. Here, the system500is employed on a network search server502. The pipeline504includes the crawler, parser and builder, but a gallery classifier506is remote from the server502. Additionally, the gallery classifier506includes a criteria component508that provides a default set of criteria, and other criteria that can be added.

FIG. 6illustrates an implementation of a client-based gallery search system600according to an aspect. Here, the system600can be employed on a desktop computing system602, portable computer, portable wireless device, or the like. The desktop system602includes a crawler/parse/builder pipeline604, where, in this case, a parser606also can include a gallery classifier608, a criteria component610, and other classifiers612. Parser output is as described herein, passed to an index builder614for index building, and ultimately, presentation via a gallery UI.

FIG. 7illustrates an implementation of a search engine pipeline system700which includes a confirmation component702in accordance with another aspect. Here, the system700includes a parser704that interfaces to an external gallery classifier706, and which classifier706that further interfaces to a criteria component708for criteria access and processing. The confirmation component702monitors many different characteristics in order to determine if a gallery page returned from a search could actually be a gallery page. For example, click behavior in a web page can be monitored. Click behavior from a sample of users can be construed as an indication that a page is or is not a gallery page. If most or all of the presented images get clicked on, then they are all perhaps of similar content inferring that this could be a gallery page. If the click activity is high once the page is classified as a gallery page, this also can be a confirmation or validation that that the page is a gallery page.

The confirmation component702interfaces to the criteria component708to pass confirmation data thereto as new criteria data to be utilized by the classifier706. The confirmation component702can interface to a gallery UI710to receive and process user interaction data (e.g., user click activity, user hover activity, . . . ), and then to pass UI and user activity information to the gallery classifier706for classification processing to help in determining if a web page is a gallery page.

Referring now toFIG. 8, there is illustrated a methodology of processing user interaction data as confirmation that a web page could be a gallery page in accordance with the disclosed innovation. At800, a search for multimedia content is initiated. At802, a received web page is parsed and classified as a potential gallery page. At804, user interaction is monitored with the potential gallery page. At806, the system determines if the user interaction is sufficiently substantial based on a predetermined interaction value to warrant classifying the page as a gallery page. If so, at808, the user interaction is processed as confirmation that the web page is a gallery page. At810, the gallery page can then be tagged as a gallery page for results ranking and processing. If the user interaction is not substantial, flow is from806to812to process the page as a non-gallery page, and flow then proceeds back to802to parse and begin classification of the next page.

FIG. 9illustrates a methodology of processing user interaction as confirmation that a web page is a gallery page according to an aspect. At900, a search is initiated for multimedia content. At902, a received web page is parsed and classified as a potential gallery page. At904, user interaction with the potential gallery page is monitored. At906, substantial user interaction is processed as confirmation that the web page is a gallery page. At908, the user interaction can be included as additional criteria to be considered by the gallery classifier when determining if a web page is a gallery page.

FIG. 10illustrates a gallery classification and presentation system1000that employs a content analyzer component1002according to an aspect. As a means to further facilitate gallery page classification, the content analyzer component1002can be utilized to analyze image, video content, and/or audio content of a multimedia web page. For example, analysis of all images in the gallery can be performed to determine if the images have a face or faces in them or there are graphics in them implying that they may be clipart. In another implementation, analysis can be to a level of face recognition to determine who is actually in an image or video content. In yet another example, audio analysis can be performed and text recognition can be performed on any text of the web page. Thus, face detection, face recognition, audio analysis (e.g., all music), text OCR'ing (optical character recognition processing), text analysis, orientation analysis for images and videos, etc., can all factor in to help in determining whether the web page is a gallery page.

FIG. 11illustrates a methodology of analyzing image content of a web page for classification purposes according to an aspect. At1100, a search is initiated for multimedia content. At1102, a received web page is parsed into structure data. At1104, image analysis is performed on image content (e.g., face recognition, face detection . . . ). At1106, based on the analysis results, the web page is classified as either a gallery page or a non-gallery page.

FIG. 12illustrates a methodology of analyzing audio content of a web page for classification purposes according to an aspect. At1200, a search is initiated for multimedia content. At1202, a received web page is parsed into structure data. At1204, audio analysis is performed on audio content (e.g., voice, music, instrumental, style, genre . . . ). At1206, based on the analysis results, the web page is classified as either a gallery page or a non-gallery page.

FIG. 13illustrates a methodology of filtering web page results based on user preferences for classification purposes as a gallery page according to an aspect. At1300, a search is initiated for multimedia content. At1302, a received web page is parsed into structure data. At1304, page processing is performed against user preferences. The user preferences can be one or more rules that are employed to limit the types of web sites that will be returned as results, for example. Additionally, the user preferences can be given more weight in how the results are ranked for processing and/or ultimate presentation. At1306, based on the user preference information, the web page is classified as either a gallery page or a non-gallery page.

FIG. 14illustrates a system1400that employs a machine learning and reasoning (LR) component1402which facilitates automating one or more features in accordance with the subject innovation. The subject invention (e.g., in connection with criteria processing and selection) can employ various LR-based schemes for carrying out various aspects thereof.

A classifier, in this context of learning and reasoning, is a function that maps an input attribute vector, x=(x1, x2, x3, x4, xn), to a class label class(x). The classifier can also output a confidence that the input belongs to a class, that is, f(x)=confidence(class(x)). Such classification can employ a probabilistic and/or statistical-based analysis (e.g., factoring into the analysis utilities and costs) to prognose or infer an action that a user desires to be automatically performed.

A support vector machine (SVM) is an example of a classifier that can be employed. The SVM operates by finding a hypersurface in the space of possible inputs that splits the triggering input events from the non-triggering events in an optimal way. Intuitively, this makes the classification correct for testing data that is near, but not identical to training data. Other directed and undirected model classification approaches include, e.g., naïve Bayes, Bayesian networks, decision trees, neural networks, fuzzy logic models, and probabilistic classification models providing different patterns of independence can be employed. Classification as used herein also is inclusive of statistical regression that is utilized to develop models of priority.

As will be readily appreciated from the subject specification, the subject invention can employ classifiers that are explicitly trained (e.g., via a generic training data) as well as implicitly trained (e.g., via observing user behavior, receiving extrinsic information). For example, SVM's are configured via a learning or training phase within a classifier constructor and feature selection module. Thus, the classifier(s) can be employed to automatically learn and perform a number of functions, including but not limited to determining according to a predetermined criteria when to employ content analysis, what content analysis should be employed for a given web page, what criteria should be considered for a gallery classification process (e.g., user preference, history file data, favorites data, . . . ), and so on. In another example, the LR component1402can monitor user interaction of a first user, and use this interaction data to affect gallery page classification in a manner that can be different from a second user.

In another example, the LR component1402, when employed on a web search server, can monitor user activity and/or interaction of a large number of users, and cluster user data, as well as web page results based on confirmation data from the larger number of users. Subsequent access to those web addresses (or URLs) will result in a high probability that the web page is a gallery page, or not a gallery page.

This are only but a few examples of the learning and reasoning that can be gained from the LR component1402in the context of gallery page search processing in accordance with the subject innovation. It is within contemplation of this innovation that many more related functions can be processed for automation and learning. For example, the LR component can learn that repeated placement and/or orientation of images on a web page, and thereafter confirmed as a gallery page can be included as additional criteria that is feed back to the criteria component for consideration for gallery page classification.

FIG. 15illustrates an image gallery page UI1500for presenting gallery images in accordance with an innovative aspect. Today, when a user searches for images (or audio or video), the user can get a page of thumbnail images which point to various other pages that are potentially text filled, news filled, or image filled, for example. If the user is looking to browse images/audio/video (a likely scenario considering the user explicitly interacted with the UI to search image content), then the user should be connected sooner to the desired end result of galleries.

A way of displaying the gallery results to a user is described. In the UI ofFIG. 15, it can be seen that image galleries can be bubbled up to the top of the search results, and can be visually differentiated. This makes it easier for the user to quickly search and discover relevant browsing results. Additionally, the galleries can be called out as special and potentially more relevant than other search results (e.g., ranked). Furthermore, the user can manually configure the engine to only show relevant galleries.

The gallery page1500includes an Images selection1502in a selection area1504wherein once selected by the user, only gallery pages with image content will be presented. Here, the Images selection1502has been selected by the user, thereby causing presentation of only image content. Categories or groupings of image content are presented as graphical indicia1506in an Image Galleries section1508. The graphical indicia1506can be presented as shadowed or double image offset graphics icons, for example, which can be selected to present corresponding individual sets or groups of images1510in a lower Images section1512.

Here, a first image gallery group1514has been selected causing the associate images1510to be presented in a reduced format in the Images section1512. The user can scroll through the associated images1512via a scroll bar1516. The selected first gallery group1514can be presented to the user in any number of different ways, as being the gallery group that was selected. For example, the first group icon1514can be presented as bolded, or colored in a different way, for example.

The selection area1504illustrated includes various user selections, as well as a search input box1518so that the user can search the presented set of images1510according to text or other metadata that can be associated with each of the images1510.

FIG. 16illustrates a video gallery page UI1600for presenting gallery video content in accordance with an innovative aspect. In the UI ofFIG. 16, it can be seen that video galleries can be bubbled up to the top of the search results, and can be visually differentiated. This makes it easier for the user to quickly search and discover relevant browsing results. Additionally, the galleries can be called out as special and potentially more relevant than other search results (e.g., ranked). Furthermore, the user can manually configure the engine to only show relevant galleries.

The gallery page1600includes a Galleries selection1602in a selection area1604wherein once selected by the user, only gallery pages will be presented. This made possible by a drop-down menu1606that is activated when the user either selects the Galleries selection or hovers over the Galleries selection with a pointing device cursor, for example. Here, the Video gallery selection from the menu1606has been selected by the user, thereby causing presentation of only video gallery content. Categories or groupings of video content are presented as graphical indicia1608in a Video Galleries section1610. The graphical indicia1608can be presented as shadowed or double image offset graphics icons, for example, which can be selected to present corresponding individual sets or groups of video files1612in a lower Video section1614.

Here, a first video gallery group1616has been selected causing the associated video content (depicted with icon or video snapshots for example)1612to be presented in a reduced format in the Video section1614. The user can scroll through the associated images icons1612via a scroll bar1618. The selected first gallery group1616can be presented to the user in any number of different ways, as being the gallery group that was selected. For example, the first group icon1616can be presented as bolded, or colored in a different way, for example.

The selection area1604illustrated includes various user selections, as well as a search input box1620so that the user can search the presented set of video files according to text or other metadata that can be associated with each of the video graphical representations1612.

FIG. 17illustrates an audio gallery page UI1700for presenting gallery audio content in accordance with an innovative aspect. In the UI ofFIG. 17, it can be seen that audio galleries can be bubbled up to the top of the search results, and can be visually differentiated. This makes it easier for the user to quickly search and discover relevant browsing results. Additionally, the galleries can be called out as special and potentially more relevant than other search results (e.g., ranked). Furthermore, the user can manually configure the engine to only show relevant galleries.

The gallery page1700includes a Galleries selection1702in a selection area1704wherein once selected by the user, only gallery pages will be presented. This made possible by a drop-down menu1706that is activated when the user either selects the Galleries selection or hovers over the Galleries selection with a pointing device cursor, for example. Here, the Audio gallery selection from the menu1706has been selected by the user, thereby causing presentation of only audio gallery content. Categories or groupings of audio content are presented as graphical indicia1708in an Audio Galleries section1710. The graphical indicia1708can be presented as shadowed or double image offset graphics icons, for example, which can be selected to present corresponding individual sets or groups of audio files1712in a lower Audio section1714.

Here, a first audio gallery group1716has been selected causing the associated audio content (depicted with icon or image snapshots for example)1712to be presented in a reduced format in the Audio section1714. The user can scroll through the associated audio icons1712via a scroll bar1718. The selected first gallery group1716can be presented to the user in any number of different ways, as being the gallery group that was selected. For example, the first group icon1716can be presented as bolded, or colored in a different way, for example.

The selection area1704illustrated includes various user selections, as well as a search input box1720so that the user can search the presented set of audio files according to text or other metadata that can be associated with each of the audio file graphical representations1712.

FIG. 18illustrates a gallery page UI1800for presenting all gallery content in accordance with an innovative aspect. In the UI ofFIG. 18, it can be seen that audio, video, and image galleries can be bubbled up to the top of the search results, and can be visually differentiated. This makes it easier for the user to quickly search and discover relevant browsing results. Additionally, the galleries can be called out as special and potentially more relevant than other search results (e.g., ranked). Furthermore, the user can manually configure the engine to only show relevant galleries.

The gallery page1800includes a Galleries selection1802in a selection area1804wherein once selected by the user, only gallery pages will be presented. This made possible by a drop-down menu1806that is activated when the user either selects the Galleries selection or hovers over the Galleries selection with a pointing device cursor, for example. Here, the All gallery selection from the menu1806has been selected by the user, thereby causing presentation of all gallery content. Categories or groupings of gallery content are presented as graphical indicia1808in a Galleries section1810. The graphical indicia1808can be presented as shadowed or double image offset graphics icons, for example, which can be selected to present corresponding individual sets or groups of gallery files1812in a lower content type section1814.

Here, a first audio gallery group1818has been selected causing the associated audio content (depicted with icon or image snapshots for example)1812to be presented in a reduced format in the type section1814. The user can scroll through the associated audio icons1812via a scroll bar1818. The selected first gallery group1816can be presented to the user in any number of different ways, as being the gallery group that was selected. For example, the first group icon1816can be presented as bolded, or colored in a different way, for example.

The selection area1804illustrated includes various user selections, as well as a search input box1820so that the user can search the presented set of audio files according to text or other metadata that can be associated with each of the audio file graphical icon representations1812.

FIG. 19illustrates a gallery page UI1900for presenting all gallery content as a listing in accordance with an innovative aspect. In the UI ofFIG. 19, it can be seen that audio, video, and image galleries can be bubbled up to the top of the search results, and can be visually differentiated. This makes it easier for the user to quickly search and discover relevant browsing results. Additionally, the galleries can be called out as special and potentially more relevant than other search results (e.g., ranked). Furthermore, the user can manually configure the engine to only show relevant galleries.

Instead of configuring the UI to present graphical icons for gallery content, the user can select a tabular representation. Here, the multimedia search results are listed near the top of the listing, and have been identified and classified as gallery content or non-gallery content. For example, two sets of audio gallery pages have been listed, as well as an image gallery page, and two non-gallery pages. The user can select a single file or multiple files for presentation in accordance with the previous web page UI's provided supra.

Referring now toFIG. 20, there is illustrated a block diagram of a computer operable to execute gallery page searching, classification and presentation in accordance with a novel aspect. In order to provide additional context for various aspects thereof,FIG. 20and the following discussion are intended to provide a brief, general description of a suitable computing environment2000in which the various aspects of the innovation can be implemented. While the description above is in the general context of computer-executable instructions that may run on one or more computers, those skilled in the art will recognize that the innovation also can be implemented in combination with other program modules and/or as a combination of hardware and software.

With reference again toFIG. 20, the exemplary environment2000for implementing various aspects includes a computer2002, the computer2002including a processing unit2004, a system memory2006and a system bus2008. The system bus2008couples system components including, but not limited to, the system memory2006to the processing unit2004. The processing unit2004can be any of various commercially available processors. Dual microprocessors and other multi-processor architectures may also be employed as the processing unit2004.

The system bus2008can be any of several types of bus structure that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. The system memory2006includes read-only memory (ROM)2010and random access memory (RAM)2012. A basic input/output system (BIOS) is stored in a non-volatile memory2010such as ROM, EPROM, EEPROM, which BIOS contains the basic routines that help to transfer information between elements within the computer2002, such as during start-up. The RAM2012can also include a high-speed RAM such as static RAM for caching data.

The computer2002further includes an internal hard disk drive (HDD)2014(e.g., EIDE, SATA), which internal hard disk drive2014may also be configured for external use in a suitable chassis (not shown), a magnetic floppy disk drive (FDD)2016, (e.g., to read from or write to a removable diskette2018) and an optical disk drive2020, (e.g., reading a CD-ROM disk2022or, to read from or write to other high capacity optical media such as the DVD). The hard disk drive2014, magnetic disk drive2016and optical disk drive2020can be connected to the system bus2008by a hard disk drive interface2024, a magnetic disk drive interface2026and an optical drive interface2028, respectively. The interface2024for external drive implementations includes at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies. Other external drive connection technologies are within contemplation of the subject innovation.

A number of program modules can be stored in the drives and RAM2012, including an operating system2030, one or more application programs2032, other program modules2034and program data2036. All or portions of the operating system, applications, modules, and/or data can also be cached in the RAM2012. It is to be appreciated that the innovation can be implemented with various commercially available operating systems or combinations of operating systems.

A user can enter commands and information into the computer2002through one or more wired/wireless input devices, e.g., a keyooard2038and a pointing device, such as a mouse2040. Other input devices (not shown) may include a microphone, an IR remote control, a joystick, a game pad, a stylus pen, touch screen, or the like. These and other input devices are often connected to the processing unit2004through an input device interface2042that is coupled to the system bus2008, but can be connected by other interfaces, such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, etc.

A monitor2044or other type of display device is also connected to the system bus2008via an interface, such as a video adapter2046. In addition to the monitor2044, a computer typically includes other peripheral output devices (not shown), such as speakers, printers, etc.

The computer2002may operate in a networked environment using logical connections via wired and/or wireless communications to one or more remote computers, such as a remote computer(s)2048. The remote computer(s)2048can be a workstation, a server computer, a router, a personal computer, portable computer, microprocessor-based entertainment appliance, a peer device or other common network node, and typically includes many or all of the elements described relative to the computer2002, although, for purposes of brevity, only a memory/storage device2050is illustrated. The logical connections depicted include wired/wireless connectivity to a local area network (LAN)2052and/or larger networks, e.g., a wide area network (WAN)2054. Such LAN and WAN networking environments are commonplace in offices and companies, and facilitate enterprise-wide computer networks, such as intranets, all of which may connect to a global communications network, e.g., the Internet.

When used in a LAN networking environment, the computer2002is connected to the local network2052through a wired and/or wireless communication network interface or adapter2056. The adaptor2056may facilitate wired or wireless communication to the LAN2052, which may also include a wireless access point disposed thereon for communicating with the wireless adaptor2056.

When used in a WAN networking environment, the computer2002can include a modem2058, or is connected to a communications server on the WAN2054, or has other means for establishing communications over the WAN2054, such as by way of the Internet. The modem2058, which can be internal or external and a wired or wireless device, is connected to the system bus2008via the serial port interface2042. In a networked environment, program modules depicted relative to the computer2002, or portions thereof, can be stored in the remote memory/storage device2050. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers can be used.

Referring now toFIG. 21, there is illustrated a schematic block diagram of an exemplary computing environment2100that supports gallery page searching, classification and presentation in accordance with another aspect. The system2100includes one or more client(s)2102. The client(s)2102can be hardware and/or software (e.g., threads, processes, computing devices). The client(s)2102can house cookie(s) and/or associated contextual information by employing the subject innovation, for example.

The system2100also includes one or more server(s)2104. The server(s)2104can also be hardware and/or software (e.g., threads, processes, computing devices). The servers2104can house threads to perform transformations by employing the invention, for example. One possible communication between a client2102and a server2104can be in the form of a data packet adapted to be transmitted between two or more computer processes. The data packet may include a cookie and/or associated contextual information, for example. The system2100includes a communication framework2106(e.g., a global communication network such as the Internet) that can be employed to facilitate communications between the client(s)2102and the server(s)2104.

Communications can be facilitated via a wired (including optical fiber) and/or wireless technology. The client(s)2102are operatively connected to one or more client data store(s)2108that can be employed to store information local to the client(s)2102(e.g., cookie(s) and/or associated contextual information). Similarly, the server(s)2104are operatively connected to one or more server data store(s)2110that can be employed to store information local to the servers2104.

What has been described above includes examples of the disclosed innovation. It is, of course, not possible to describe every conceivable combination of components and/or methodologies, but one of ordinary skill in the art may recognize that many further combinations and permutations are possible. Accordingly, the innovation is intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims. Furthermore, to the extent that the term “includes” is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim.