Abstract:
Systems and methods are provided to augment the search results of a search operation are provided. The method enhances a user&#39;s experience by identifying and displaying information within the search results which is of a remarkable value. Such information may be presented with a different presentation semantics from the rest of the search result. Such presentation semantics being indicative of the remarkability of the information.

Description:
CROSS REFERENCE TO RELATED APPLICATION 
       [0001]    This application claims priority to U.S. Provisional Application Ser. No. 61/950,253 entitled Search Results Display filed on Mar. 10, 2014, which is incorporated herein by reference. 
     
    
     TECHNICAL FIELD 
       [0002]    The present disclosure generally relates to search engine operations and methods to display the results of a search operation. Particularly, the disclosure relates to a system and method for augmenting the results of a search operation by identifying for the user information in the results that is of a remarkable nature. 
       BACKGROUND 
       [0003]    The statements in this section merely provide background information related to the present disclosure and may not constitute prior art. 
         [0004]    It is commonly required in the field of Information Technology to provide a service that searches through data sources. The data source herein may refer to data and/or document(s) on the Internet, intranet, storage devices, and so on. In order to use a search engine, a user seeking information on a desired topic generally inputs a search query consisting of keyword(s) or phrase(s) relevant to the topic into the search interface of the search engine. In response, the search engine typically displays a report with a prioritized list of links pointing to relevant documents containing the search keywords. Oftentimes, a short summary of text i.e., extract/snippet is also included for each result. The extract/snippet is that portion or portions of the text in the document that contain the keywords from the search query. In addition, to facilitate easy understanding of the search results, the keyword(s) from the search query contained in the extracts may be highlighted. 
         [0005]    US 20120150861 A1 disclosed a method of identifying answers to search queries and highlighting the answers when they appear in search results. This is however limited to the answers in the snippet merely to direct the user&#39;s attention to the answers. 
         [0006]    While highlighting the keywords and answers in search results is helpful, it is not sufficient in fully understanding the search results. A drawback in such limited highlighting in the search results is that it does not help the user in understanding the significance of the information in the search results, thereby making the results less useful to the user. 
         [0007]    Another drawback of the existing search results is that it takes the user considerable amount of time and effort to understand the found results. There are no clues in the search results which will help the user to quickly identify remarkable information within the search results. 
         [0008]    In view of the above drawbacks, there remains a need for an effective method of searching data sources for useful information relating to topics of interest. 
       SUMMARY 
       [0009]    The following presents a simplified summary of the disclosure in order to provide a basic understanding to the reader. This summary is not an extensive overview of the disclosure and it does not identify key/critical elements of the disclosure or delineate the scope of the disclosure. Its sole purpose is to present some concepts disclosed herein in a simplified form as a prelude to the more detailed description that is presented later. 
         [0010]    The present disclosure generally relates to methods and systems for searching data sources for information. Particularly, the invention relates to a computer implemented method of augmenting the search results in a multi-document search environment, said method comprising (a) Identifying remarkable data (a) Predefining identification rules for said remarkable data (c) Storing in a storage unit at least one such identification rule; wherein the identification rule comprises attributes selected from the group comprising a key, a value, classification, clarification and combinations thereof (d) Identifying at least one such remarkable data within the search results (e) highlighting at least a portion of the remarkable data within the search results. 
         [0011]    A remarkable data in accordance with the invention is to be interpreted broadly to include any value associated with a key that is of a remarkable nature as determined by the system. The classification attribute in the identification rule identifies the type of such remarkable data and may be selected from the group comprising a good value, a bad value, a record, and combinations thereof. The clarification attribute in the identification rule gives additional information regarding the remarkable data. 
         [0012]    In one embodiment of the invention, the remarkable data within the search results are highlighted based on the identification rule. In a preferred embodiment, the remarkable data within the search results is highlighted based on the classification attribute of the identification rule. 
         [0013]    Depending on the classification, different presentation semantics could be applied to the remarkable data. The presentation semantics selected from the group comprising font color, font size, font weight, font family, text decorations, borders, shading and combinations thereof. 
         [0014]    In another embodiment, the clarification attribute is appended to the search result. The clarification attribute is appended to the search result by a graphical user interface element. In a preferred embodiment, wherein the graphical user interface element is a tool tip. 
         [0015]    In a preferred embodiment of the present invention, remarkable data with similar classification attributes are presented with similar presentation semantics across all search results. 
         [0016]    In another aspect of the present disclosure is provided with a system comprising search engine unit. The search engine unit may comprise one or more logics configured to perform the functions and operations associated with the above-disclosed methods. 
         [0017]    In another aspect of the present disclosure is provided a computer program product executable in a memory of a search engine unit 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0018]    The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in anyway. Throughout the disclosure, like elements are represented by like reference numerals, which are given by way of illustration only and thus are not limitative of the various embodiments. 
           [0019]    Other objects and advantages of the present disclosure will become apparent to those skilled in the art upon reading the following detailed description of the preferred embodiments, in conjunction with the accompanying drawings, wherein: 
           [0020]      FIG. 1  is a block diagram illustrating an exemplary search environment in accordance with an embodiment of the present disclosure. 
           [0021]      FIG. 2  is a block diagram of an exemplary computing device of  FIG. 1 . 
           [0022]      FIG. 3  depicts exemplary rules for the identification of remarkable data. 
           [0023]      FIG. 4  depicts exemplary rules for highlighting remarkable data. 
           [0024]      FIG. 5  depicts an exemplary search operation illustrating identifying and highlighting remarkable data in accordance with the present disclosure. 
           [0025]      FIG. 6  is a flow diagram of a method of displaying search results comprising highlighting of remarkable data in accordance with one or more embodiments. 
       
    
    
     DETAILED DESCRIPTION 
       [0026]    It is to be understood that the present disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The present disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. 
         [0027]    The use of “including”, “comprising” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced item. Further, the use of terms “first”, “second”, and “third”, and the like, herein do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. 
         [0028]    The disclosure described here is equally applicable to searching and returning links to any document containing text and optional presentation semantics (the look and feel instructions) such as, but not limited to, HTML, DHTML, XML, SGML, PDF, E-mail, Microsoft® Word documents, Microsoft® Power point documents, news group postings, multimedia objects, Graphics Interchange Format images and/or Shockwave Flash files. 
         [0029]    Through the length of the specification and claims, the words “extract” and “snippet” are used interchangeably. 
         [0030]      FIG. 1  depicts a search environment  100  in accordance with an exemplary embodiment of the present disclosure. It will be understood and appreciated by those of ordinary skill in the art that the computing system architecture  100  shown in  FIG. 1  is merely an example of one suitable computing system and is not intended to suggest any limitation as to the scope of use or functionality of the present invention. Neither should the computing system architecture  100  be interpreted as having any dependency or requirement related to any single module/component or combination of modules/components illustrated therein. 
         [0031]    The system  100  comprises a search engine unit  110 , a client  120  and a storage unit  140 . The search engine unit  110 , the client  120  and the storage unit  140  all communicate over a network  130 . 
         [0032]    The network  130  can include any type of network known in the art or future-developed. In this regard, the network  130  may be an Ethernet, a local area network (LAN), or a wide area network (WAN), e.g., the Internet, or a combination of networks. 
         [0033]    The search engine unit  110  may be a dedicated or shared server including but not limited to any type of application server, database server, or file server configurable and combinations thereof. The search engine unit  110  and the client  120  may include, but are not limited to, a computer, handheld unit, mobile unit, consumer electronic unit, or the like. 
         [0034]    The exemplary search engine unit  110  comprises search engine logic  111 , search result parsing logic  112  and search result highlighting logic  113 . 
         [0035]    In the exemplary search engine unit  110 , the search engine logic  111  may be configured to identify and construct search results for a search query. 
         [0036]    The search engine unit  110  further comprises the search result parsing logic  112 . The search result parsing logic  112  may be configured to identify keys and corresponding to each key associated value within search results. The search result parsing logic  112  identifies key/values by looking at the clues within the search result or clues from the document that the search result is extracted from. The clues may include, but not limited to, presentation semantics, format, sentence structure, natural language processing (NLP) of the search result text or the search result text in the document. 
         [0037]    In addition, the search result parsing logic  112  may be configured to identify remarkable data among the identified key/values. The process of identifying remarkable data is further explained with reference to  FIG. 3  and  FIG. 5 . 
         [0038]    The remarkable data within the search results identified by the search result parsing logic  112  may be highlighted and augmented by the search result highlighting logic  113 . 
         [0039]    The storage unit  140  is configured to store information associated with search results, remarkable data identification rules, highlighting rules, or the like. In various embodiments, such information may include, without limitation, domains, URLs, webpages, websites, indexes, identification rules, highlighting rules, information associated therewith, and the like. In embodiments, the storage unit  140  is configured to be searchable for one or more of the items stored in association therewith. It will be understood and appreciated by those of ordinary skill in the art that the information stored in association with the storage unit  140  may be configurable and may include any information relevant to search results and highlighting of remarkable data, or the like. The content and volume of such information are not intended to limit the scope of embodiments of the present disclosure in any way. Further, though illustrated as a single, independent component, the storage unit  140  may, in fact, be a plurality of storage units, for instance a database cluster, portions of which may reside on the search engine unit  110 , the client  120 , another external computing device (not shown), and/or any combination thereof. The single unit depictions are meant for clarity, not to limit the scope of embodiments in any form. 
         [0040]    A user  122  through the client logic  121  on the client  120  may enter a search query consisting of keyword(s) which may identify the type of information that the user is interested in retrieving. The client logic  121  may comprise, for example, an Internet browser; however, other types of client logic  121  for interfacing with the user  122  and for communicating with the search engine unit  110  may be used in other embodiments of the present disclosure. The client logic  121  transmits the user search query to the search engine unit  110  via the network  130 . Upon receiving the user search query the search engine unit  110  examines the storage unit  140  and compiles a prioritized list of search results with remarkable data within the search results highlighted and returns the search results to the client logic  121  which displays the results to the user  122  in a window. 
         [0041]    In some preferred embodiments, the search engine unit  110  is shown in  FIG. 2 . It should be noted, however, that embodiments are not limited to implementation on such computing devices, but may be implemented on any of a variety of different types of computing units within the scope of embodiments hereof. The search engine unit  110  (as shown in  FIG. 1 ) is only one example of a suitable computing/search environment and it is not intended to suggest any limitation as to the scope of use or functionality of the disclosure. 
         [0042]    In some embodiments, the search engine unit  110  may include a bus  206 , a processor  201 , memory  202 , network device  203 , input device  204 , and an output device  205 . Bus  206  may include a path that permits communication among the components of the search engine unit  110 . 
         [0043]    The memory  202  stores the search engine logic  111 , the search result parsing logic  112 , and the search result highlighting logic  113  as software in memory  202 . 
         [0044]    The memory  202  may be any type of computer memory known in the art or future-developed for electronically storing data and/or logic, including volatile and non-volatile memory. In this regard, memory  202  can include random access memory (RAM), read-only memory (ROM), flash memory, any magnetic computer storage unit, including hard disks, floppy discs, or magnetic tapes, and optical discs. 
         [0045]    The processor  201  comprises processing hardware for interpreting or executing tasks or instructions stored in memory  202 . Note that the processor  201  may be a microprocessor, a digital processor, or other type of circuitry configured to run and/or execute instructions. 
         [0046]    The network device  203  may be any type of network unit (e.g., a modem) known in the art or future-developed for communicating over a network  130  ( FIG. 1 ). In this regard, the search engine unit  110  ( FIG. 1 ) communicates with the storage unit  140  ( FIG. 1 ) and the client  120  ( FIG. 1 ) over the network  130  ( FIG. 1 ) via the network device  203 . 
         [0047]    The input device  204  is any type of input unit known in the art or future-developed for receiving data. As an example, the input unit  204  may be a keyboard, a mouse, a touch screen, a serial port, a scanner, a camera, or a microphone. 
         [0048]    The output device  205  may be any type of output unit known in the art or future-developed for displaying or outputting data. As an example, the output device  205  may be a liquid crystal display (LCD) or other type of video display unit, a speaker, or a printer. 
         [0049]    Note that the disclosure may also be practiced in a distributed computing environment where tasks or instructions of search engine unit  110  ( FIG. 1 ) are performed by multiple computing units communicatively coupled to the network. 
         [0050]    Further note that, the search engine unit  110  ( FIG. 1 ) components may be implemented by software, hardware, firmware or any combination thereof. In the exemplary search engine unit  110 , depicted by  FIG. 1 , all the components are implemented by software and stored in memory  202 . 
         [0051]      FIG. 3  depicts a portion of exemplary identification rules  300  stored in the storage unit  140  ( FIG. 1 ) and made available to the search engine unit  110  ( FIG. 1 ) to identify remarkable data within the search results. 
         [0052]    The identification rules  300  comprise of keys and corresponding to each key a value. For each key and value combination in identification rules  300 , there may be optional additional information which may further classify and clarify identified remarkable data. 
         [0053]    An identification rule in  300  may identify and narrowly classify data instead of a broad classification. For example, an identification rule may identify data as remarkable data and narrowly classify as excellent, very good, good, etc. instead of a broad classification as good. Another identification rule may identify data as remarkable data and narrowly classify as world record, national record, regional record etc., instead of a broad classification as record. 
         [0054]    Exemplary identification rule  301  comprises of key “ODI Score” and the corresponding value “50-100”. This key/value combination represents a range of values between “50” and “100”. This rule may identify any ODI score value between “50” and “100” in text as remarkable data with “Bad” classification and “Low Score” as the clarification for the identification. 
         [0055]    Exemplary identification rule  304  comprises of key “Loreum Ipsum Population” and the corresponding value “45 million”. This rule may identify Loreum Ipsum population value in text as remarkable data with “World Record” classification and “Top Ranked City In Terms of Population” as the clarification for the identification. 
         [0056]    Exemplary identification rule  306  comprises of key “Award” and the corresponding value “Medal of Honor”. This rule may identify any award with value medal of honor in text as remarkable data with “Excellent” classification and the “US Highest Military Honor” as the clarification for the identification. 
         [0057]    Note that the identification rules  300  may be compiled manually or compiled automatically by parsing data sources using NLP techniques known in the art. 
         [0058]    In the exemplary embodiment of the present disclosure, each remarkable data in search results may be presented to the user in different presentation semantics based on the remarkable data classification. In this regard, presentation semantics rules for each classification may be stored in the storage unit  140  ( FIG. 1 ). 
         [0059]      FIG. 4  shows a portion of exemplary presentation semantics rules  400  that may be applied for various classifications. From the presentation semantics rules  400 , remarkable data classified as “Bad” may be shown in red color. Thus, remarkable data identified by the identification rules  301  and  302  ( FIG. 3 ) may be shown in red color. 
         [0060]    Note that the presentation semantics may not be limited to font color and text decoration. In other embodiments, presentation semantics may include, but not limited to, font weight, font family, background color, borders, shading etc. 
         [0061]    Note that in other embodiments, all or some of the classifications may share the same presentation semantics. 
         [0062]      FIG. 5  depicts a GUI  500  with a portion of search results that is displayed to the user  122  ( FIG. 1 ) by the client logic  121  ( FIG. 1 ) with remarkable data highlighted as a result of the user searching for keywords “Loreum Ipsum”  501 . 
         [0063]    Upon receiving the search query  501 , the search engine logic  111  ( FIG. 1 ) compiles a list of search results from the storage unit  140  ( FIG. 1 ). One such result  502  is shown in the GUI  500 . Within the search result  502 , the search result parsing logic  112  ( FIG. 1 ) identifies “Population”  504  as a key and “44.89 million”  505  as its corresponding value based on the sentence structure where these two words are separated by a “:”. In this example, the search result parsing logic  112  ( FIG. 1 ) identifies the word before “:” as the key and the word after “:” as the value. However, when the search result parsing logic  112  ( FIG. 1 ) tries to match the key “Population”  504  found in search result  502  with a key from the identification rules  300  ( FIG. 3 ), no match is found. The search result parsing logic  112  ( FIG. 1 ) then parses the title  503  using NLP and finds two nouns “City” and “Loreum Ipsum” and searches identification rules  300  ( FIG. 3 ) for a matching key by appending each noun to the key “Population”  504 . The key of identification rule  304  ( FIG. 3 ) matches the combination “Loreum Ipsum” and “Population”. Since broad classification for rule  304  is record, no value comparison is necessary and the key  504  value  505  is identified as remarkable data by the identification rule  304  ( FIG. 3 ). 
         [0064]    Key “Air Quality Index”  506  and the corresponding value “900”  507  are matched to the identification rule  303  ( FIG. 1 ). In this case, the search result parsing logic  112  ( FIG. 1 ) finds the match based on both the key and the value combination. The key “Air Quality Index”  506  is an exact match to the identification rule  303  key and the value “900”  507  matches the value criteria of “&gt;800” in the identification rule  303 . Hence, this key/value pair is identified as remarkable data with a classification of “Very Bad”. 
         [0065]    Similarly, key “Literary Index”  508  and corresponding value “89”  509  is identified as remarkable data by the identification rule  305  and the classification is “Very Good”. 
         [0066]    Each key/value pair in the search result  502  is considered remarkable data if at least one matching identification rule is identified by the search result parsing logic  112  ( FIG. 1 ). 
         [0067]    Note that for some of the key/value pairs in search results no matching key(s) may be found in identification rules  300  ( FIG. 3 ). Hence, these key/value pairs will not be considered remarkable data. 
         [0068]    Note that the search result parsing logic  112  ( FIG. 1 ) may understand all the variations for a key. For example, the search result parsing logic  112  ( FIG. 1 ) may recognize “Population of Loreum Ipsum” and “Population Loreum Ipsum” as “Loreum Ipsum Population”. In another embodiment, all the variations may be stored in storage unit  140  ( FIG. 1 ) and made available to the search result parsing logic  112  ( FIG. 1 ). 
         [0069]    For each remarkable data identified by the search result parsing logic  112  ( FIG. 1 ) in the search result  502 , the search result highlighting logic  113  ( FIG. 1 ) identifies the classification from the corresponding matching identification rule. Based on the classification, the search result highlighting logic  113  ( FIG. 1 ) identifies a highlighting rule and applies the presentation semantics from the highlighting rule to the remarkable data in the search result  502 . 
         [0070]    Key “Population”  504  and value “44.89 million”  505  is classified as “World Record” in its corresponding matching identification rule  304  ( FIG. 3 ). Based on the “Word Record” classification, the search result highlighting logic  113  ( FIG. 1 ) identifies highlighting rule  403  ( FIG. 4 ) and applies presentation semantics of the highlighting rule  403  ( FIG. 4 ) to the remarkable data value  505 . Note that in GUI  500  the color of the remarkable data value  505  is orange and is underlined. 
         [0071]    Similarly, for Key “Air Quality Index”  506  and value “900”  507  is classified as “Very Bad” in its corresponding matching identification rule  303  ( FIG. 3 ). Based on the “Very Bad” classification, the search result highlighting logic  113  ( FIG. 1 ) identifies highlighting rule  401  ( FIG. 4 ) and applies presentation semantics of the highlighting rule  401  ( FIG. 4 ) to the remarkable data value  507 . Note that in GUI  500  the color of the remarkable data value  507  is dark red. 
         [0072]    For key “Literacy Index”  508  and value “89”  509  is classified as “Very Good” in its corresponding matching identification rule  305  ( FIG. 3 ). Based on the “Very Good” classification, the search result highlighting logic  113  ( FIG. 1 ) identifies highlighting rule  402  ( FIG. 4 ) and applies presentation semantics of the highlighting rule  402  ( FIG. 4 ) to the remarkable data value  509 . Note that in GUI  500  the color of the remarkable data value  509  is dark blue. 
         [0073]    Note that in other embodiments the presentation semantics may be applied to both keys and values. In yet another embodiment the presentation semantics may be applied only to keys. 
         [0074]    Note that in those cases where clarifications for identification rules are available, the search result highlighting logic  113  ( FIG. 1 ) may append the clarifications from the remarkable data identification rules to the search results containing the remarkable data. In the exemplary embodiment, the search result highlighting logic  113  ( FIG. 1 ) appends clarification attribute of the identification rule for the remarkable data to the value of the remarkable data by the tool tip graphical user interface element. Thus, when the user moves the cursor over the remarkable data value  505 , the identification rule  304  ( FIG. 3 ) clarification attribute pops up on the GUI  500  next to the remarkable data value  505 . 
         [0075]    In one embodiment, a legend may be included in the GUI  500  to indicate the presentation semantics associated with each classification. 
         [0076]      FIG. 6  is a flow chart illustrating one method in accordance with the present disclosure. In step  601 , the search engine unit  110  ( FIG. 1 ) may accept the search query comprising of keyword(s)/search term(s). In step  602 , the search engine unit  110  ( FIG. 1 ) may find search results matching search query criteria. For each search result, steps  603  and  604  may be performed by the search engine unit  110  ( FIG. 1 ). In step  603 , the search result parsing logic  112  ( FIG. 1 ) may identify remarkable data within the search result text with the aid of identification rules. In step  604 , the search result highlighting logic  113  ( FIG. 1 ) for each remarkable data in the search result identifies highlighting rule based on the classification of the remarkable data and applies presentation semantics from the highlighting rule to the remarkable data. In step  605 , the search results with remarkable data highlighted may be returned. 
         [0077]    The claimed subject matter has been provided here with reference to one or more features or embodiments. Those skilled in the art will recognize and appreciate that, despite of the detailed nature of the exemplary embodiments provided here, changes and modifications may be applied to said embodiments without limiting or departing from the generally intended scope. These and various other adaptations and combinations of the embodiments provided here are within the scope of the disclosed subject matter as defined by the claims and their full set of equivalents.