Microsoft Technology Licensing, LLC

Linkedin Corporation

Other

Pinterest, Inc.

Farid Hosseini

Sanaz Ahari

Sarthak D Shah

Christina Allen

Brian W MacDonald

Nikhil Dandekar

Michael Maxwell Cameron

Xiaoxin Yin

Adam D Troy

Sarah Jean Culberson Alpern

M Christopher Pruet

Dan Fain

Ahmad A Abdulkader

Nitin Agrawal

Tabreez Govani

Bo-June Hsu

Girish Kumar

Robert A Williams

Gloria Lau

Maxim V Stepin

Ankur Gupta

Seth McLaughlin

Vijay Nair

Ada Yu

Jason A Bolla

Mohammad Omid Monshizadeh

Joyce Wang

Nazan Khan

Giridhar Kumaran

Daniel C Fain

Salil Shah

Systems and methods are presented for adding system-identified content to a user's content space based on information identified from the user's email account. In operation, after obtaining user authorization to access email items of an email account, the email items are iteratively processed. In processing each of the email items, one or more topics of a currently processed email item are identified. Based on the identified topics and user preferences, one or more content items may be identified for addition to the user's online content space. Additionally, the information identified from processing the one or more email items is used to update the user's preferences.

Generating personalized content

A system and computing instructions may include a user device, a social network database, and a processor. The user device may include a user interface configured to display a web browser. The social network database may be configured to store social network information related to an entity. The processor may be configured to identify the entity based on content of a webpage displayed on the web browser of the user device, obtain social network information related to the entity from the social network database based on a social network relationship between the user and the entity, and display the social network information on the web browser of the user device.

Displaying social networking information based on identified entity

Computer-readable media and computerized methods are provided for identifying terms associated with one or more queries, including aspects directed to manipulating a list of terms associated with a query class by extracting terms, identifying equivalences or relevant terms, and condensing or expanding the list of terms. In embodiments, synonymous terms can be identified. An updated list of terms can be written to a storage location in association with a query or query class.

Identifying terms associated with queries

During an analysis technique, a cohort of individuals is identified based on a set of attributes. Significance metrics for the individuals in the cohort are calculated based on profiles of the individuals and behaviors of the group of individuals, which includes the cohort, when interacting with the profiles. For example, a significance metric for a given individual may include a number of views of a profile of the given individual, by a group of individuals, during a time interval and/or a number of connection requests to the profile of the given individual, by the group of individuals, during the time interval. Based on the significance metrics, the subset of the individuals may be identified. This subset may include individuals that have achieved career milestones exceeding those of the other individuals in the cohort (e.g., notable individuals).

Aggregating content related to a notable individual

Method, apparatus, and articles of manufacture for presenting a decision user interface to a first member of a social network service, receiving information identifying a set of interests of the first member entered at the decision user interface, searching at least one of the group consisting or profiles of members of the social network service and user decision interfaces presented to members of the social network service and, responsive to searching, providing information relating to the set of interests to the first member. The set of interests may include a field of study or an organization or an academic degree.

Methods and systems for providing decision-making support

Methods, systems, algorithms, and media are provided for disambiguating entities present in a received search query. Lists of categories from semi-structured data from external sites as well as internal sources are used to detect if ambiguity exists in an entity within the search query. Multiple senses or categories of the ambiguous entity are determined by ascertaining the primary intent of an entity extracted from a main term of a document. The probability of each sense is calculated by computing a total amount of traffic received for each of the senses of the ambiguous entity. The sense with the highest amount of computed traffic is the most probable determined sense.

Disambiguation of entities

A first member of a social network service provides a set of desired attributes and a designation of the type of a candidate having the desired attributes that is desired as a recommendation. The attributes of the profiles of other members of the social networks are searched for entities having the set of desired attributes. At least one of the entities having the desired attributes that result from the search is presented to the first member as the recommendation of a candidate. The first member may provide a second set of desired attributes and a designation of the type of at least one second candidate having the second set of desired attributes. The attributes of the profiles of the other members of the social network may be searched for second entities having the second set of desired attributes. The first member is presented with at least one of the second entities as the recommendation of a second candidate.

Using attributes on a social network for decision-making support

Computer-readable media, computer systems, and computing methods are provided for classifying search results as either of good quality or of poor quality. Initially, a portion of the search results, such as the highest ranked documents, are selected for evaluation. A level of quality for each of the selected search results is determined using a classification process that includes the following steps: targeting features demonstrated by the selected search results to be evaluated; evaluating the selected features to generate a level-of-quality score for each of the selected search results; comparing the score against a predefined threshold value; and, based on the comparison, assigning each of the selected search results an absolute measurement. The absolute measurement indicates poor quality when the score is less than the threshold value. Upon recognizing that the selected search results are of poor quality, automatically executing a corrective action that reformulates the issued search query.

Classifying results of search queries

A technique for identifying a group of potential candidates to join an organization is described. During this analysis technique, an identifier is received from an individual. This identifier may be used to associate the individual with a pre-existing profile that includes information. For example, the identifier may include a link to the pre-existing profile. Alternatively, a profile with the information may be generated for the individual based on the identifier and an information source. Using the information, an affinity metric of the individual with the organization is calculated, such as a number of employees of the organization who know the individual or who attended a same educational institution as the individual. Moreover, the affinity metric is used to determine whether to include the individual in the group of potential candidates to join the organization. In this way, the analysis technique may facilitate more-efficient recruiting efforts.

Digital method of recruitment

The present invention is directed to presenting a suggested search query. Responsive to receiving a user-devised search parameter, a suggested search query is identified. The user-devised search parameter might have been previously received by a search system, or alternatively, might be a unique query that has not been previously received. A suggested search query might be generated using various techniques, such as by applying an n-gram language model. A classification of the suggested search query is determined, and the suggested search query is presented together with a visual indicator, which signifies the classification.

Generating and presenting a suggested search query

Computer-readable media and computerized methods for automatically organizing search results according to task groups are provided. The methods involve aggregating a gallery of entities (e.g., search queries that share a common categorization) into a query class and assigning a dictionary (e.g., list of terms that are drawn from various sources) to the query class. The task groups are identified from the list of terms within the dictionary. The process of identification includes analyzing patterns of user search behavior to select terms from the list of terms, which reflect popular user search intents, and ranking the selected terms based on predetermined parameters to produce an ordering. Based on the ordering, a set of the selected terms that are highest ranked are declared the task groups. The task groups are employed to arrange the search results on a UI display and to provide a consistent and intuitive format for refining a search.

Identifying task groups for organizing search results

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San Francisco, CA, United States of America

Farid Hosseini