Abstract: Techniques are provided for automatically creating online accounts based on digital images, such as digital images of business cards. In one technique, multiple data items that have been extracted from a digital image of a business card are identified. A particular data item is contact information of a user associated with (or identified by) the business card. A verification code is sent, based on the particular data item, to a computing device of the user. The verification code is received from the computing device of the user. In response to receiving the verification code an account is created for the user and the account is modified to include a least some of the multiple data items.

Abstract: Techniques for determining a location of an entity are described. A determination module using member profile data may determine the location of the entity. Member profile data can include information about a member's employer and the employer's location. The determination module accesses member profiles from a social network. Additionally, the determination module may create a subgroup of entity-related member profiles from the accessed member profiles. The entity-related member profiles can be associated with a specific entity. Furthermore, the determination module may determine a suggested location for the specific entity based on location information derived from the related member profiles. Moreover, the determination module may calculate a connection density for the specific entity based on connections associated with the entity-related member profiles.

Abstract: Techniques for determining a location of an entity are described. A determination module using member profile data may determine the location of the entity. Member profile data can include information about a member's employer and the employer's location. The module accesses member profiles from a social network. Additionally, the module may create a subgroup of entity-related member profiles from the accessed member profiles. The entity-related member profiles can be associated with a specific entity. Furthermore, the module may determine a suggested location for the specific entity based on location information derived from the related member profiles. Moreover, the module may calculate a connection density for the specific entity based on connections associated with the entity-related member profiles. Subsequently, the module may determine that the suggested location is a physical location when the calculated connection density is above a pre-determined threshold value.

Abstract: In an example embodiment, a web page is obtained using a web page address stored in a first record and is parsed to extract one or more images from the web page along with a first plurality of features for each of the one or more images from the web page. Information about each image of the web page and the extracted first plurality of features for the web page are input into a supervised machine learning classifier to calculate a logo confidence score for each image of the web page, the logo confidence score indicating the probability that the image is an organization logo. In response to a particular image in the web page having a logo confidence score transgressing a first threshold, the particular image is injected into an organization logo field of the first record.

Abstract: In an example embodiment, a web page is obtained using a web page address stored in a first record and is parsed to extract one or more images from the web page along with a second plurality of features for each of the one or more images from the web page. Information about each image of the web page and the extracted second plurality of features for the web page are input into a supervised machine learning classifier to calculate a logo confidence score for each image of the web page, the logo confidence score indicating the probability that the image is an organization logo. In response to a particular image in the web page having a logo confidence score transgressing a first threshold, the particular image is injected into an organization logo field of the first record.

Abstract: Techniques are provided for automatically creating online accounts based on digital images, such as digital images of business cards. In one technique, multiple data items that have been extracted from a digital image of a business card are identified. A particular data item is contact information of a user associated with (or identified by) the business card. A verification code is sent, based on the particular data item, to a computing device of the user. The verification code is received from the computing device of the user. In response to receiving the verification code an account is created for the user and the account is modified to include a least some of the multiple data items.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein for Candidate Predictor Engine (“C.P. Engine”) instantiates data structure(s) modeled according to a plurality of job candidate predictor decision trees. The C.P. Engine encodes data representing a job candidate context feature set based on an attribute(s) of a target candidate account and an attribute(s) of a job posting. The C.P. Engine filters each respective feature from the job candidate context feature set through a job candidate predictor decision tree that corresponds to a same job candidate context feature type as the respective feature. The C.P. Engine generates prediction output based on each result of filtering through the job candidate predictor decision trees. The prediction output indicates a likelihood of the target candidate account being qualified for the job posting.

Abstract: A system and method for generating content based on network source features are provided. In example embodiments, a request for a landing page that shows a display of one or more electronic documents is received. The source of the landing page and the one or more electronic documents is analyzed to determine page view correlation data and selection correlation data. The page view correlation data and selection correlation data is used to generate rank data for the electronic documents. The electronic documents are sorted according to the rank data and a display of the electronic documents in sorted order is provided.

Abstract: Techniques are provided for generating and deploying a computer model with relatively few inputs from a user. Techniques are also provided for creating a data mart that multiple computer models may leverage in order to decrease the time required to generate subsequent computer models.

Abstract: Techniques are provided for generating and deploying a computer model with few inputs from a user. Techniques are also provided for creating a data mart that multiple computer models may leverage in order to decrease the time required to generate subsequent computer models.

Abstract: In an example embodiment, an organization name is retrieved from an organization name field of a first record. A web search is performed using the organization name, producing web search results. A second plurality of features is extracted for each web search result in the set of web search results. Each of the extracted second plurality of features for each web search result in the set of web search results is input into a supervised machine learning classifier to classify each of the web search results in the set of web search results as either containing an organization web address or not containing an organization web address. In response to a determination by the supervised machine learning classifier that a first web search result contains an organization web address, the organization web address from the first web search result is injected into an organization web address field of the first record.

Abstract: In an example embodiment, a fuzzy join operation is performed by, for each pair of records, evaluating a first plurality of features for both records in the pair of records by calculating term frequency-inverse term frequency (TF-IDF) for each token of each field relevant to each feature and based on the calculated TF-IDF for each token of each field relevant to each feature, computing a similarity score based on the similarity function by adding a weight assigned to the TF-IDF for any token that appears in both records.

Abstract: In an example embodiment, a web page is obtained using a web page address stored in a first record and is parsed to extract one or more images from the web page along with a second plurality of features for each of the one or more images from the web page. Information about each image of the web page and the extracted second plurality of features for the web page are input into a supervised machine learning classifier to calculate a logo confidence score for each image of the web page, the logo confidence score indicating the probability that the image is an organization logo. In response to a particular image in the web page having a logo confidence score transgressing a first threshold, the particular image is injected into an organization logo field of the first record.

Abstract: In an example embodiment, a member profile corresponding to a member of a social networking service is obtained. Usage information for the member is then obtained, and one or more member metrics are calculated based on the member profile and usage information for the corresponding member. A plurality of features are extracted from the member profile and the one or more member metrics. The plurality of features is inserted into an organization name confidence score model to obtain a confidence score for an organization name in the member profile.

Abstract: Techniques are provided for automatically creating online accounts based on digital images, such as digital images of business cards. In one technique, multiple data items that have been extracted from a digital image of a business card are identified. A particular data item is contact information of a user associated with (or identified by) the business card. A verification code is sent, based on the particular data item, to a computing device of the user. The verification code is received from the computing device of the user. In response to receiving the verification code an account is created for the user and the account is modified to include a least some of the multiple data items.

Abstract: Techniques are provided for automatically creating online accounts based on digital images, such as digital images of business cards. In one technique, multiple data items that have been extracted from a digital image of a business card are identified. A particular data item is contact information of a user associated with (or identified by) the business card. A verification code is sent, based on the particular data item, to a computing device of the user. The verification code is received from the computing device of the user. In response to receiving the verification code an account is created for the user and the account is modified to include a least some of the multiple data items.

Abstract: Methods and systems for generating tailored user interface presentations based on skills clusters and automatically modified member profiles are presented. According to various embodiments, a set of skills are accessed and a skills matrix generated. A set of co-occurrences among the set of skills are identified. A set of skills clusters is automatically generated based on identifying of the co-occurrences and the skills clusters are automatically validated. A graphical representation of the validated skills cluster is presented with user interface elements for modifying the validated skills cluster and data representing member profiles is presented based on the validated skills cluster.

Abstract: In an example embodiment, a method is provided where information regarding a member of a social networking service and a job opening are obtained. Then information about a plurality of courses available for the member to take is obtained, the information including cost, time, and a vector including, for each of a plurality of skills identified in a member profile of the member, an effect of taking the corresponding course. A subset selection algorithm is then used to select an optimal combination of courses selected from the plurality of courses, based on minimizing cost and time while maximizing cumulative increase in odds of the member successfully obtaining the job opening from taking the selected courses.

Abstract: In an example embodiment, a method is provided to calculate a distance for a first member of a social networking service and a job opening, which indicates the likelihood that the first member will obtain the job. The distance is calculated by applying one or more policies to member profiles of members who applied for similar jobs to obtain a hypothetical perfect candidate for the job. The member's profile is then automatically compared to the hypothetical perfect candidate profile to calculate the distance.

Abstract: A member profile including a vector containing a field for each of a plurality of skills and a rating of one or more of the skills in the vector for a member of a social networking service is obtained. A first distance indicating a vector distance between the vector of the member profile and a vector of a hypothetical member profile representing the perfect job candidate is obtained. A hypothetical member profile for the member is created by combining the vector of the member profile with the indication of how each of the one or more skills is improved through taking the course from course information. A second distance between the member and the hypothetical perfect candidate for the job is obtained, and the difference between the first distance and the second distance is calculated to determine an estimate of how much the course will increase the member's job chances.