Abstract: A multi-horizon predictor system that predicts a future parameter value for multiple horizons based on time-series data of the parameter, external data, and machine-learning. For a given time horizon, a time series data splitter splits the time into training data corresponding to a training time period, and a validation time period corresponding to a validation time period between the training time period and the given horizon. A model tuner tunes the prediction model of the given horizon fitting an initial prediction model to the parameter using the training data thereby using machine learning. The model tuner also tunes the initial prediction model by adjusting an effect of the external data on the prediction to generate a final prediction model for the given horizon using the validation data. A multi-horizon predictor causes the time series data splitter and the model tuner to operate for each of multiple horizons.

Abstract: Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and spiking URLs with increased user interest. History data, provided from browser applications residing on users' computers that indicate URLs accessed by the users, is parsed to identify new/previously unknown URLs. The history data also indicates URLs in which there is increased interest based on a number of recent hits as compared to an average number of hits determined over time. Author postings of new URLs to social networking sites and a quality rating of the authors may also be used to identify and filter new URLs. Search indexes are updated with the new and spiking URL data. As such, lag time between posting of new URLs and spiking of URL interest and inclusion of this data in a search index is greatly decreased.

Abstract: Systems, methods, computer storage media, and user interfaces are provided for providing analytics tools derived from a consumer decision journey model. Once the consumer decision journey for a particular good or service is constructed, a series of tools is provided to help a user understand the return on investment for providing different types of multimedia content at different stages in the consumer decision journey for a particular demographic. To do so, an interface is provided to the user that enables the user to select a desired tool and features of the tool the user wishes to exploit. Browser history from a plurality of consumers is transformed into a visual representation that provides insights into the types of multimedia content that can provide the greatest return on investment for a particular demographic at a particular state in the consumer decision journey for the selected category of goods or services.

Abstract: Methods, systems, and media are provided for delivering clustered search results for recent and non-recent events by maintaining the identification (ID) numbers of the respective clustered documents beyond the “fresh” life span of the clustered documents. When clusters are formed according to similar content, an ID number and associated attributes are assigned to each of the clusters. This provides a mechanism to track and retrieve the respective clusters for subsequent delivery of search results. The respective ID numbers of the clusters are maintained, even after the documents are no longer considered “fresh.” These similar-content clusters are further subdivided according to publication date. This provides individual subdivided clusters for similar content events that occurred at different time spans, which are delivered along with individual non-clustered search results in a SERP.

Abstract: A multi-horizon predictor system that predicts a future parameter value for multiple horizons based on time-series data of the parameter, external data, and machine-learning. For a given time horizon, a time series data splitter splits the time into training data corresponding to a training time period, and a validation time period corresponding to a validation time period between the training time period and the given horizon. A model tuner tunes the prediction model of the given horizon fitting an initial prediction model to the parameter using the training data thereby using machine learning. The model tuner also tunes the initial prediction model by adjusting an effect of the external data on the prediction to generate a final prediction model for the given horizon using the validation data. A multi-horizon predictor causes the time series data splitter and the model tuner to operate for each of multiple horizons.

Abstract: Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and spiking URLs with increased user interest. History data, provided from browser applications residing on users' computers that indicate URLs accessed by the users, is parsed to identify new/previously unknown URLs. The history data also indicates URLs in which there is increased interest based on a number of recent hits as compared to an average number of hits determined over time. Author postings of new URLs to social networking sites and a quality rating of the authors may also be used to identify and filter new URLs. Search indexes are updated with the new and spiking URL data. As such, lag time between posting of new URLs and spiking of URL interest and inclusion of this data in a search index is greatly decreased.

Abstract: Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and spiking URLs with increased user interest. History data, provided from browser applications residing on users' computers that indicate URLs accessed by the users, is parsed to identify new/previously unknown URLs. The history data also indicates URLs in which there is increased interest based on a number of recent hits as compared to an average number of hits determined over time. Author postings of new URLs to social networking sites and a quality rating of the authors may also be used to identify and filter new URLs. Search indexes are updated with the new and spiking URL data. As such, lag time between posting of new URLs and spiking of URL interest and inclusion of this data in a search index is greatly decreased.

Abstract: Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and with metadata for new and known URLs. Data associated with communications made by users using a social network is received. The communications include a URL therein that a user has shared, posted, or otherwise communicated to one or more other users using the social network. When the URL is not found in a search index it is identified as a new URL and is added to the search index. A measure of a trending interest, or virality, of the URL is determined from the data. The determined virality is associated with the URL in a search index as metadata. The virality is useable to inform a ranking of the URL against a plurality of other URLs for identification and presentation as a search result in a search engine results page.

Abstract: Systems, methods, and computer-readable storage media are provided for identifying dominant entity categories associated with target entities. A target entity is received and plural data sources are utilized to determine entity categories of which the target entity is a member and an initial confidence score for each of the entity categories. Each initial confidence score represents the likelihood that the associated entity category is a dominant category for the target entity. At least one data source includes information pertaining to plural entities arranged in a graph-based ontology that includes identifiers of respective entity categories of which the subject entities are members. Graph-based confidence score propagation is then utilized to incorporate information regarding entities determined to be related to the target entity and accolades associated with the target entity to alter the initial confidence scores provided for various entity categories of which the target entity is a member.

Abstract: Methods, systems, and computer-storage media for improving the freshness, or the apparent freshness, of search results are described. In an embodiment, the first portion of search results presented on a search results page are based on responsiveness to the search query and a second portion of results describe only recently published documents that are responsive to the search query. In an embodiment, a more recent version of the document, which is not directly used to determine responsiveness, is used to build the caption for a search result. Another way to make search results appear fresh is to include a publication time within the search result caption. In one embodiment, the publication time is generated by calculating a point in time between when a document is first added to a search index and the previous time the search engine visited the site where the document was found.

Abstract: Methods, systems, and media are provided for delivering clustered search results for recent and non-recent events by maintaining the identification (ID) numbers of the respective clustered documents beyond the “fresh” life span of the clustered documents. When clusters are formed according to similar content, an ID number and associated attributes are assigned to each of the clusters. This provides a mechanism to track and retrieve the respective clusters for subsequent delivery of search results. The respective ID numbers of the clusters are maintained, even after the documents are no longer considered “fresh.” These similar-content clusters are further subdivided according to publication date. This provides individual subdivided clusters for similar content events that occurred at different time spans, which are delivered along with individual non-clustered search results in a SERP.

Abstract: A client application installed on end user computers generates metadata from the content of web pages visited by end users and provides the metadata to a search engine. When an end user visits a web page, the end user's computer downloads and displays the web page to the end user. The client application may simultaneously access the web page content and generate this metadata in the form of a content signature of the web page from the web page content. The client application then provides the content signature to a search engine. The search engine may employ content signatures to identify new web pages to crawl and index. Additionally, the search engine may employ content signatures to identify changes to web pages and determine the crawl frequency of web pages.

Abstract: Methods, systems, and media are provided for delivering clustered search results for recent and non-recent events by maintaining the identification (ID) numbers of the respective clustered documents beyond the “fresh” life span of the clustered documents. When clusters are formed according to similar content, an ID number and associated attributes are assigned to each of the clusters. This provides a mechanism to track and retrieve the respective clusters for subsequent delivery of search results. The respective ID numbers of the clusters are maintained, even after the documents are no longer considered “fresh.” These similar-content clusters are further subdivided according to publication date. This provides individual subdivided clusters for similar content events that occurred at different time spans, which are delivered along with individual non-clustered search results in a SERP.

Abstract: Filters are generated by analyzing a set of search results most relevant to a search query to determine filter values that may be of most interest to the user. A search query is received and is classified into a query segment that best corresponds to the search query so that filter categories associated with the query segment can be identified. Based on an analysis of search results most relevant to the search query, metadata associated with these search results is used to formulate filter values for each filter category. The filter values are ordered based on their respective frequency of presence in the search results. The search results, along with the filter categories and filter values, are communicated for presentation.

Abstract: Methods, systems, and media are provided for delivering clustered search results for recent and non-recent events by maintaining the identification (ID) numbers of the respective clustered documents beyond the “fresh” life span of the clustered documents. When clusters are formed according to similar content, an ID number and associated attributes are assigned to each of the clusters. This provides a mechanism to track and retrieve the respective clusters for subsequent delivery of search results. The respective ID numbers of the clusters are maintained, even after the documents are no longer considered “fresh.” These similar-content clusters are further subdivided according to publication date. This provides individual subdivided clusters for similar content events that occurred at different time spans, which are delivered along with individual non-clustered search results in a SERP.

Abstract: Methods and systems for determining an adaptive crawl rate for a Web crawler based on historical publication data from a Web source are provided. A frequency of publication of the Web source is determined over a specified period of time, and an adaptive crawl rate is calculated using the frequency of publication. The Web crawler is then deployed at the calculated adaptive crawl rate.

Abstract: Systems and methods for applying user behavior data to improve search query result ranking are provided. Upon receiving an update file indicating that recent, significant user behavior data is available for a document associated with an inverted index, the update file is published periodically and frequently to an index server. After filtering out the relevant update information from the update file, the index server extracts identifiers of the documents having the associated user behavior data. The update file and the identifier of the documents are utilized to update an in-memory index containing representations of metadata indicative of the user behavior. The in-memory index is continuously updated and utilized to serve search query results in response to user search queries. Search query results from the in-memory index are ranked using the user behavior data prior to serving. Thus, results associated with recent, significant user-behavior metadata receive prominent placement on the search results page.

Abstract: Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and with metadata for new and known URLs. Data associated with communications made by users using a social network is received. The communications include a URL therein that a user has shared, posted, or otherwise communicated to one or more other users using the social network. When the URL is not found in a search index it is identified as a new URL and is added to the search index. A measure of a trending interest, or virality, of the URL is determined from the data. The determined virality is associated with the URL in a search index as metadata. The virality is useable to inform a ranking of the URL against a plurality of other URLs for identification and presentation as a search result in a search engine results page.

Abstract: Methods, systems, and computer-readable media are provided for updating a search index with new uniform resource locators (URLs) and spiking URLs with increased user interest. History data, provided from browser applications residing on users' computers that indicate URLs accessed by the users, is parsed to identify new/previously unknown URLs. The history data also indicates URLs in which there is increased interest based on a number of recent hits as compared to an average number of hits determined over time. Author postings of new URLs to social networking sites and a quality rating of the authors may also be used to identify and filter new URLs. Search indexes are updated with the new and spiking URL data. As such, lag time between posting of new URLs and spiking of URL interest and inclusion of this data in a search index is greatly decreased.

Abstract: A client application installed on end user computers generates metadata from the content of web pages visited by end users and provides the metadata to a search engine. When an end user visits a web page, the end user's computer downloads and displays the web page to the end user. The client application may simultaneously access the web page content and generate this metadata in the form of a content signature of the web page from the web page content. The client application then provides the content signature to a search engine. The search engine may employ content signatures to identify new web pages to crawl and index. Additionally, the search engine may employ content signatures to identify changes to web pages and determine the crawl frequency of web pages.