Abstract: Techniques and technologies for caller assistance systems are described. In at least some embodiments, a system comprises: a processing component; and a caller assistance engine configured to receive a request from a calling device; select a menu execution path associated with the request, the menu execution path defining one or more operations to be performed to achieve an intent of the request; execute the menu execution path including execute the one or more operations to be performed to achieve the intent of the request; determine whether the intent of the request has been achieved; and when the intent of the request has been achieved, connect the calling device with the intent of the request or provide an alert to the calling device that the intent of the request has been achieved.

Abstract: Techniques and technologies for caller assistance systems are described. In at least some embodiments, a system comprises: a processing component; and a caller assistance engine configured to receive a request from a calling device; select a menu execution path associated with the request, the menu execution path defining one or more operations to be performed to achieve an intent of the request; execute the menu execution path including execute the one or more operations to be performed to achieve the intent of the request; determine whether the intent of the request has been achieved; and when the intent of the request has been achieved, connect the calling device with the intent of the request or provide an alert to the calling device that the intent of the request has been achieved.

Abstract: Social data is used to extract actions that end users perform in order to provide deeplinks for search results. Social data from social networking services may be accessed and analyzed to identify actions performed by end users. Additionally, the social data may be analyzed to identify URLs of web pages at which the actions may be performed. Information regarding the actions and corresponding URLs is stored for use by a search engine service to provide deeplinks for search results returned in response to user search queries.

Abstract: Social data is used to extract actions that end users perform in order to provide deeplinks for search results. Social data from social networking services may be accessed and analyzed to identify actions performed by end users. Additionally, the social data may be analyzed to identify URLs of web pages at which the actions may be performed. Information regarding the actions and corresponding URLs is stored for use by a search engine service to provide deeplinks for search results returned in response to user search queries.

Abstract: Search results are provided with personalized deeplinks for an end user. User behavior information is gathered regarding web pages visited by the end user. When the end user submits a search query, the website category of a search result is identified and user behavior information regarding web pages visited at other websites within the website category is identified. At least one deeplink is selected for the search result based on that user behavior information. In some instances, user behavior information may be tracked for a group of end users. The user behavior information for the group of end users may be used in conjunction with the user behavior information for the end user to facilitate deeplink selections for search results returned in response to search queries from the end user.

Abstract: Social data is used to extract actions that end users perform in order to provide deeplinks for search results. Social data from social networking services may be accessed and analyzed to identify actions performed by end users. Additionally, the social data may be analyzed to identify URLs of web pages at which the actions may be performed. Information regarding the actions and corresponding URLs is stored for use by a search engine service to provide deeplinks for search results returned in response to user search queries.

Abstract: Systems and methods for identifying trending content on one or more domains is presented. In response to receiving a request for trending content on each domain of a set of domain, network activity data corresponding to network activity of a recent period of time is obtained. According to various embodiments, the network activity data corresponds to activity in the immediately previous time period and includes any of query logs from one or more search engines, social data from one or more social network sites, and browsing data corresponding to the browsing history of a plurality of computer users. Trending content from the network activity data for each domain of the set of domains is identified and the identified content is returned in response to the received request.

Abstract: Techniques are described herein for processing social search results. Such social search results may be included in a relatively higher-ranked (e.g., a highest-ranked) subset of a user's search results and/or selected from a relatively lower-ranked subset of the user's search results in response to a determination that the relatively higher-ranked subset includes social search result(s). In one example, the social search results (or a subset thereof) may be annotated to include publicly available rich metadata. Such metadata may be extracted from user profiles on social networking domains from which the social search results are received. In another example, the social search results (or a subset thereof) may be clustered such that they are consecutively ranked. In yet another example, the social search results (or a subset thereof) may be configured to be displayed in a designated arrangement (e.g., in a grid having multiple columns).

Abstract: Search results are provided with personalized deeplinks for an end user. User behavior information is gathered regarding web pages visited by the end user. When the end user submits a search query, the website category of a search result is identified and user behavior information regarding web pages visited at other websites within the website category is identified. At least one deeplink is selected for the search result based on that user behavior information. In some instances, user behavior information may be tracked for a group of end users. The user behavior information for the group of end users may be used in conjunction with the user behavior information for the end user to facilitate deeplink selections for search results returned in response to search queries from the end user.

Abstract: Search results are provided with personalized deeplinks for an end user. User behavior information is gathered regarding web pages visited by the end user. When the end user submits a search query, the website category of a search result is identified and user behavior information regarding web pages visited at other websites within the website category is identified. At least one deeplink is selected for the search result based on that user behavior information. In some instances, user behavior information may be tracked for a group of end users. The user behavior information for the group of end users may be used in conjunction with the user behavior information for the end user to facilitate deeplink selections for search results returned in response to search queries from the end user.

Abstract: Architecture that provides results and data which are alternative (“orthogonal”) to the original (or primary) query and encourage the user to engage with dimensions of information other than, but related to, the original query intent. The architecture computes the original intent of original search query, computes a category of the original query based on the original intent, computes a target document (result) of a domain based on the query intent, determines if orthogonal intent is desired, computes an alternative document result of the domain related to the intent, and presents content associated with the alternative document result.

Abstract: Systems and methods for identifying trending content on one or more domains is presented. In response to receiving a request for trending content on each domain of a set of domain, network activity data corresponding to network activity of a recent period of time is obtained. According to various embodiments, the network activity data corresponds to activity in the immediately previous time period and includes any of query logs from one or more search engines, social data from one or more social network sites, and browsing data corresponding to the browsing history of a plurality of computer users. Trending content from the network activity data for each domain of the set of domains is identified and the identified content is returned in response to the received request.

Abstract: Parameterized actions are provided with search results to allow users to enter parameter values and perform the actions directly from the search results. By analyzing websites in a category, a parameterized action available at the websites and common parameters may be identified. When an end user performs a search that returns a web page result from a website having the parameterized action, an indication of the parameterized and common parameters may be provided as part of the search result. Additionally, user interface elements may allow the end user to enter parameter values to perform the parameterized action directly from the search result. In some instances, user context may be employed to pre-populate parameter values in the search result.

Abstract: Architecture that automatically employs web search user query data to identify the places (e.g., locations, businesses) to which people are likely traveling, and then produces a heatmap visualization of the most popular places in the local area on a local map in a mapping application, which is then viewable in the vertical listing of the search results. This data can be utilized to rank local businesses in terms of popularity by knowing how many people are actually visiting the business as a function of date (and perhaps time). The web search data, which is used to understand the popular locations of a geographical area, includes signals such as searching for directions in the map application, and analyzing directions-related terms such as “From” and “To” in the search results. Another signal can be a location or business search which triggers an appropriate instant answer.

Abstract: A method, system, and medium are provided to temporally bias items included in a search results webpage. The items include navigational links, search results, advertisements, or any other content or items included in a search results webpage. User engagement with the items via the search-engine results page and/or other webpages is tracked. A user-engagement score and an age of the items are determined. A temporal-bias factor is calculated using a decay function that increases in intensity with the age of the items. A rank score is calculated for each item based on the user-engagement score and the temporal-bias factor—the temporal-bias factor decreasing the rank score as a function of the age of the items. The items are ranked based at least in part on the rank score and one or more of the items are chosen for presentation in a search-engine results page.

Abstract: Techniques are described herein for using intent to access a domain (i.e., domain intent) to provide more search results that correspond to the domain. For example, a rule may specify a maximum number of search results that are allowed to be provided from a domain (or a host that corresponds to the domain) in response to a search query. Each search query may include any number of ngrams. An ngram is a subsequence of elements in a sequence (e.g., a search query). An intent to access a domain may be determined based on one or more of the ngrams in a search query. A number of search results that correspond to a domain may be increased to be greater than the maximum number based on one or more of the ngrams that are included in the search query being associated with the intent to access the domain.

Abstract: Techniques are described herein for using intent to access a domain (i.e., domain intent) to provide more search results that correspond to the domain. For example, a rule may specify a maximum number of search results that are allowed to be provided from a domain (or a host that corresponds to the domain) in response to a search query. Each search query may include any number of ngrams. An ngram is a subsequence of elements in a sequence (e.g., a search query). An intent to access a domain may be determined based on one or more of the ngrams in a search query. A number of search results that correspond to a domain may be increased to be greater than the maximum number based on one or more of the ngrams that are included in the search query being associated with the intent to access the domain.

Abstract: Techniques are described herein for processing social search results. Such social search results may be included in a relatively higher-ranked (e.g., a highest-ranked) subset of a user's search results and/or selected from a relatively lower-ranked subset of the user's search results in response to a determination that the relatively higher-ranked subset includes social search result(s). In one example, the social search results (or a subset thereof) may be annotated to include publicly available rich metadata. Such metadata may be extracted from user profiles on social networking domains from which the social search results are received. In another example, the social search results (or a subset thereof) may be clustered such that they are consecutively ranked. In yet another example, the social search results (or a subset thereof) may be configured to be displayed in a designated arrangement (e.g., in a grid having multiple columns).

Abstract: Action-based search results are provided that include deeplinks to a particular action to allow an end user to view various locations for performing that action and to quickly access those locations to perform the action. In some instances, when a search query is received, the search query may be identified as corresponding with a particular action. Action-based search-results with deeplinks to locations for performing that action are identified and returned. In other instances, traditional search results may be provided in response to a search query. One of the search results may include an action-based deeplink for a particular action. An action-pivot link may be provided for that action that, when selected, causes action-based search results for that action to be identified and returned for presentation to the end user.

Abstract: Search results are provided with personalized deeplinks for an end user. User behavior information is gathered regarding web pages visited by the end user. When the end user submits a search query, the website category of a search result is identified and user behavior information regarding web pages visited at other websites within the website category is identified. At least one deeplink is selected for the search result based on that user behavior information. In some instances, user behavior information may be tracked for a group of end users. The user behavior information for the group of end users may be used in conjunction with the user behavior information for the end user to facilitate deeplink selections for search results returned in response to search queries from the end user.