Apple Inc.

Topsy Labs, Inc.

Rishab Aiyer Ghosh

Vipul Ved Prakash

Lun Cui

Thomas James Emerson

Olga Iosifovna Gurevich

Saravana Kumar Siva Kumaran

Charles Henry Salzenberg, Jr

Scott Park Manley

Vipal Ved Prakash

A new approach is proposed that contemplates systems and methods to identify geographic locations of all social media content items retrieved form a social network in real time, wherein the geographic locations are physical locations from which the social media content items are originated or authored. If the latitude/longitude (geographic) coordinates of the content item are available, the geographic location of the social media content item can be identified using such geographic coordinates. For content items which geographic coordinates are not available, historical archive of content items with high-confidence of geographic locations are utilized to train a location classifier to predict geographic locations of such content items with high accuracy. Finally, the identified locations of the content items are confirmed to be accurate and are presented to a user together with the content items.

Systems and methods for identifying geographic locations of social media content collected over social networks

A new approach is proposed that contemplates systems and methods to ascribe or transfer metadata from one search-related entity to another, where each entity can be one of subject or source, citation, and object or target. First, one or more complete or incomplete attributes associated with one or more of entities across source, citation and target are identified with a high degree of probable accuracy, wherein such metadata or attributes include but are not limited to, time, language, and location of the entities. The identified attributes are then ascribed or transferred from one entity where the metadata is available to other search entities. Finally, the transferred attributes can be utilized to facilitate the selection and ranking of the cited targets for the search result.

System and method for metadata transfer among search entities

A method and apparatus of a device that performs a multi-domain query search is described. In an exemplary embodiment, the device receives a query prefix from a client of a user. The device further determines a plurality of search completions across the plurality of separate search domains. In addition, the device ranks the plurality of search completions based on a score calculated for each of the plurality of search completions determined by a corresponding search domain, where at least one of the plurality of search completions is used to generate a plurality of search results without an indication from the user and in response to receiving the query prefix.

Multi-domain query completion

A new approach is proposed that contemplates systems and methods to examine and determine quality of objects cited by citations in a search result based on a citation graph that includes citing subjects, citations, and cited objects. First, influence scores of a plurality of subjects/sources that compose the citations of the objects in the search result are calculated. The quality of the objects cited by the subjects can then be determined by examining the influence scores for the subjects of the citations. Finally, the cited objects selected can be presented to a user or provided to a thirty party for further processing together with the relevant citations and citing subjects.

System and method for determining quality of cited objects in search results based on the influence of citing subjects

A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

System and method for query temporality analysis

A new approach is proposed that contemplates systems and methods to provide a ranking of cited objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of 'experts' on 'topics' without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.

Search of sources and targets based on relative expertise of the sources

A new approach is proposed that contemplates systems and methods to generate customized subjective search results from the perspective of a user who conducts the search or any other subject entity of chosen by the user. A scored subject list is created from the user's network of sources/subjects/contacts, where each element on the list is a subject/source and the score reflects the subject's potential influence or closeness of its connection/relation with the user. Once created, the subject list is then used as a bias filter on the list of citations from search results. With such influence-weighted citation scores, objects and/or subjects from citations of subjects that have big influence on or enjoy high respect from the user will be ranked prominently in the search result presented to the user, thus biasing the search results from the user's perspective.

System and method for customizing search results from user's perspective

A new approach is proposed that contemplates systems and methods to generate customized search results as well as metrics, such as aggregated sentiment, counts of targets or sources or citations, or aggregated gross impressions or exposure, of social media content items over a social network while discriminating between the perspectives of individuals from the media and individuals not from the media. This approach can be used to generate search results and/or metrics including only media perspectives, or excluding media perspectives. More specifically, while social media content items are retrieved from corpus based on certain search criteria, for the purpose of providing search results or providing aggregated metrics, the search criteria can include a media or non-media filter, which is applied to the authors posting social media content to exclude or include certain authors meeting media/non-media criteria. For the application of a non-media filter, content from media authors can be excluded, or ranked below content from non-media authors. Similarly, for a media filter, content from non-media authors can be excluded, or ranked below content from media authors.

System and method for customizing analytics based on users media affiliation status

A new approach is proposed that contemplates systems and methods to provide the ability to detect, measure, aggregate, and normalize sentiments expressed by a group of users on a certain event or topic on a social network so that the normalized sentiments truly reflect the sentiments of the general public on that specific event or topic. Additionally, the collected and measured sentiments of an individual user expressed on a social network can also be normalized against a baseline sentiment that reflects in order to truly reflect the individual user's sentiment at the time of his/her expression.

Systems and methods for sentiment detection, measurement, and normalization over social networks

A new approach is proposed that contemplates systems and methods to provide a ranking of citied objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of 'experts' on 'topics' without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.

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San Francisco, CA, United States of America

Rishab Aiyer Ghosh