Patent Application
20080005118
Embodiments of the present invention are described in detail below with reference to the attached drawing figures, which are incorporated by reference herein and wherein:
The subject matter of the present invention is described with specificity to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the term “step” may be used herein to connote different elements of methods employed, the term should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly described. Further, the present invention is described in detail below with reference to the attached drawing figures, which are incorporated in their entirety by reference herein.
Embodiments of the present invention provide methods, systems, and computer-readable media for automatically displaying a structured-search-results user interface in response to unstructured search queries. Exemplary embodiments will be discussed first, followed by a discussion of an exemplary operating environment with reference to
The data store 225 can store any type of information. This information may include web content, web-search results, images, news, facts, and other types of information commonly found on the web, for example. The data store 225 may also include advertising content. The search engine component 220 is operative to traverse the data store 225 to obtain search results in response to search queries. The search engine component 220 is capable of determining which search results are most relevant to particular search queries. Those skilled in the art will recognize that various search utilities exist in the art and that any of these known search techniques may be used. For example, the search engine component 220 may use search terms contained in the search query to identify matching terms contained in potential search results stored in data store 225. And, as potential results are considered, the search engine component 220 may use a relevancy-ranking heuristic to determine which potential results should be selected. Again, such search techniques and relevancy-ranking heuristics are well known in the art, and the present invention is not limited to any particular search algorithm.
The search engine component 220 is further operative to analyze search results to determine whether a structure threshold is satisfied. For example, in embodiments of the present invention, the search engine component determines whether search results have schemas with attributes that overlap sufficiently to meet a structure threshold. If common fields appear in the search results with a sufficiently high frequency, the search engine component 220 will determine that a structure threshold has been satisfied. The threshold can be based on a minimum absolute count of results or on a minimum percentage of the results. In an embodiment, the search engine component 220 is operative to perform a “second-pass” analysis to extract common attributes from the search results. These common attributes can be offered to the user as search-refinement options to allow the user to further narrow search results. For example, the search engine component 220 may identify a common attribute of “price” in the search results. In an embodiment, the search engine component 220 instructs the interface component 215 to display price as a search-refinement option to the user after having identified price as a common attribute in the search results. In doing so, the search engine component 220 takes advantage of structure present in the search results to offer search-refinement options to the user. Various methods of indexing and searching structured data present in potential web-search results are known in the art. For example, the search engine component 220 may use meta-tags, such as search tags, to identify potential structure present in the search results. The meta-tags may contain name-value pairs that can be used by the search engine component 220 to determine whether the structure threshold is satisfied. The search engine component 220 may also search attributes contained in pages coded using an XML schema. These pages might be coded using any type of XML schema, such as Document Type Definition (DTD) or XML Schema. If a sufficient number of the search results have similar name-value pairs sharing common field names such as name, price, or category then the search engine component 220 may determine that the structure threshold is satisfied. This process will be described in further detail below with reference to
In another embodiment, the search engine component 220 analyzes the structure identified in the search results to determine whether a variance threshold has been satisfied. For example, if language is identified as a common attribute across the search results sufficient to satisfy the structure threshold, then language can be offered as a search-refinement option. But, if the search results all have the same attribute of being in the English language, then this attribute is not a useful search-refinement option. By employing a variance threshold, search engine component 220 can determine whether particular identified, shared attributes vary sufficiently across the search results to satisfy a variance threshold. In this embodiment, if the variance threshold is satisfied for a particular attribute, then the attribute is used to offer a search-refinement option to the user.
At a step 304, search results are obtained based on the search query. This may be performed, for example, by the search engine component 220 performing any type of search algorithm to traverse the data stored in data store 225. Methods of obtaining search results using a search engine are well known in the art, and the present invention is not limited to any particular search technique. After a list of search results is obtained that have been deemed relevant to the search query, at a step 306 the search results are analyzed to identify any shared-structure elements present in the search results. Again, any method for identifying structure present in search results may be used. These shared-structure elements can be, for example, similar name-value pairs contained in meta-tags or XML code, overlapping schema attributes, or any other shared-structure elements. These shared-structure elements could also be a common field name such as price, product name, category, rating, author, or any other field name.
At a step 308, the identified shared-structure elements are used to determine whether sufficient shared-structure elements are present in the search results to satisfy a structure threshold. The structure threshold designates a minimum amount of structure that must be present in the search results to justify displaying search-refinement options to the user based on the identified shared-structure elements. The structure threshold can be an absolute minimum number of search results that must have one or more shared-structure elements or it can be a minimum percentage or proportion of the total search results that must have the shared-structure elements in order to warrant display of the search-refinement options. This step ensures that the structured-search-results interface will not be displayed if there is not a sufficient amount of relevant structure present in the search results. For example, if a user enters a search query of “Nissan Altima,” the search results obtained for “Nissan Altima” will be analyzed to identify any shared-structure elements present. The elements of price, year, and mileage may be identified as shared structure elements. The method 300 will then determine whether sufficient search results contain these shared-structure elements. For example, the method 300 may determine that 75% of the thirty most-relevant search results contain the shared-structure elements of price, year, and mileage. If the structure threshold requires that a minimum of 50% of the thirty-most relevant results contain the shared-structure elements, then the structure threshold is satisfied in this case.
At a step 310, if the structure threshold is satisfied, a structured search results interface is automatically displayed. In an embodiment, the structured search results user interface displays search-refinement options based on the identified structure on a common display with the search results. In another embodiment, search-refinement options are offered after identifying relevant structure and also determining whether the search results exhibit sufficient variety with regard to particular identified structural attributes. For example, if all of the search results are for “Nissan Altima,” then a variance threshold can be employed to determine that the results do not vary sufficiently to offer the car model attribute as a search-refinement option. Exemplary user interfaces will be described below. If the structure threshold is not satisfied, then at a step 312 the search results are displayed in an unstructured-search-results user interface that does not offer search refinement options based on structure. Most search-results user interfaces today are unstructured interfaces. A method for displaying refined search results on a structured search results interface will be discussed below with reference to
At a step 414, a structured search results interface is displayed suggesting the generated search filter to the user. For example, the user interface offers the user the option of refining the list of search results based on price. Continuing the above example, the user is offered the option of sorting the search results for “Nissan Altima” using a price range filter developed from the analysis of the structure of the search results. For example, the search filter allows the user to narrow the search results to display only those results with a price attribute having values falling within the range of $20,000 and $30,000. Or, the user can be offered a search filter allowing the user to narrow the search results by a year attribute to display only results having a year value of 2005, for example. If the method 400 determines that the set of highly-relevant search results does not have at least one common structure attribute then an unstructured search results interface is displayed, which was described above. The method 400 performs a “two-pass” analysis by first searching for structure inherent in the top search results and by then second searching for repetition of the structure throughout the entire list of search results. In an embodiment, the second step of the analysis may be limited to a specified number of search results to reduce the burden of analyzing the entire list of search results.
At a step 510, an additional filter can be applied by the user. If the user requests to further refine the search results based on an additional common structure attribute, steps 506 and 508 are repeated to display the further refined search results. If the user does not specify an additional filter, at a step 512, the process ends. Now, exemplary user interfaces for displaying automatically a structured search results interface will be discussed.
Although the subject matter has been described with reference to specific exemplary embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. And, although the subject matter has been described in language specific to methodological acts, the subject matter defined in the appended claims is not necessarily limited to the specific acts described above. Rather, the specific acts described above are disclosed as example forms of implementing the claims.
Although particular exemplary user interfaces have been described, it will be evident to one of ordinary skill in the art that other user interfaces can be used without departing from the scope of the invention. And, although particular examples of structured data have been provided, the present invention is not limited to particular types of structured data.
Now, an exemplary operating environment for embodiments of the present invention will be discussed.
Referring initially to
The invention may be described in the general context of computer code or machine-useable instructions, including computer-executable instructions such as program modules, being executed by a computer or other machine, such as a personal data assistant or other handheld device. Generally, program modules including routines, programs, objects, components, data structures, etc., refer to code that perform particular tasks or implement particular abstract data types. The invention may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, more specialty computing devices, etc. The invention may also be practiced in distributed computing environments where tasks are performed by remote-processing devices that are linked through a communications network. In a distributed-computing environment, program modules may be located in both local and remote computer-storage media including memory-storage devices. The computer-useable instructions form an interface to allow a computer to react according to a source of input. The instructions cooperate with other code segments to initiate a variety of tasks in response to data received in conjunction with the source of the received data.
With reference to
Computing device 100 typically includes a variety of computer-readable media. By way of example, and not limitation, computer-readable media may comprise Random Access Memory (RAM); Read Only Memory (ROM); Electronically Erasable Programmable Read Only Memory (EEPROM); flash memory or other memory technologies; CDROM, digital versatile disks (DVD) or other optical or holographic media; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, carrier wave or any other medium that can be used to encode desired information and be accessed by computing device 100.
Memory 112 includes computer-storage media in the form of volatile and/or nonvolatile memory. The memory may be removable, nonremovable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disc drives, etc. Computing device 100 includes one or more processors that read data from various entities such as memory 112 or I/O components 120. Presentation component(s) 116 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc.
I/O ports 118 allow computing device 100 to be logically coupled to other devices including I/O components 120, some of which may be built in. Illustrative components include a microphone, joystick, game pad, satellite dish, scanner, printer, wireless device, etc. Though a particular exemplary operating environment has been discussed, many other suitable operating environments can be used.
