Abstract: A machine may be configured to generate an enhanced user interface for displaying social analytics based on viral mentions and threading. For example, the machine accesses a plurality of items of digital content. The machine extracts, for each of the plurality of items of digital content, a title that describes a particular item of digital content. The machine generates a group of items of digital content based on the extracted titles associated with the plurality of items of digital content. The machine identifies, from the group of items of digital content, an original item of digital content and one or more subsequent items of digital content. The machine determines a strength value associated with the original item of digital content. The machine generates and causes a display of an enhanced user interface that displays the title and the strength value associated with the original item of digital content.

Abstract: Techniques for delaying the transmission of a message to one or more recipients using an alert in order to provide data protection and security with respect to data included in the message are disclosed herein. In some embodiments, a computer-implemented method comprises: receiving a request to transmit a message from a computing device of a user to a recipient, the request comprising content of the message; detecting an issue with the request using at least one classifier to classify the request as having the issue; generating an alert based on the detecting of the issue; and prior to transmitting the message to a destination associated with the recipient, causing the generated alert to be displayed on the computing device of the user, the alert indicating the issue with the message.

Abstract: Method and system for identifying user expectations in question answering in an on-line social network system are described. The automated support system is configured to address the technical problem of optimization of the processing of user input submitted to a computer in the form of a natural language. The automated support system uses machine learning algorithms to automatically extract, from the user input, information indicative of the user's expectations and obtain data relevant to the input based on said information indicative of the user's expectations.

Abstract: A topical representative assessment system implements techniques for determining entities that are ambassadors for one or more topics. The ambassadors are determined based on content items that they have authored or content items that are otherwise attributed to them. An ambassador may be any type of entity such as a person, a company, or an organization. Machine analytics may be used to determine whether a content item corresponds to a specific topic, determine a sentiment for a content item, analyze feedback for a content item, or any combination of these.

Abstract: A phony profiles detector for an on-line social network system is described. The phony profiles detector uses characteristics of a profile that was associated with an indication that it represents a malicious user, a so-called seed profile, to identify other profiles that should be flagged as potentially the source of undesirable behavior. Based on the degree of similarity determined for a subject profile with respect to a seed profile, the phony profiles detector generates a malicious user indicator and stores it as associated with the subject profile.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a first configuration for processing a first set of content items from a first data source and a second configuration for processing a second set of content items from a second data source. For each content item in the first set of content items, the system uses mappings from the first configuration to transform original fields from the content item into required fields in a record representing the content item. Next, the system generates, from the required fields, a document key for the content item. The system also performs deduplication of multiple records with the document key and stores a single record with the document key. Finally, the system uses the second configuration to generate, from the second set of content items, a set of records independently of processing the first set of content items.

Abstract: In some embodiments, the disclosed subject matter involves comparing the results of natural language processing (NLP) of unstructured text to historical results for verification and validation of the NLP models/algorithms. The analysis uses statistical theory and practices to automatically monitor and validate the performances of the (NLP) algorithms on a periodic basis. Each unstructured text is run through one or more NLP algorithms and scored for relevance or contextual classification. Distribution of the scores is assumed to be Gaussian in nature so that a probability value (p-value) may be generated. When the p-value is below a threshold value, manual tagging may be initiated for the current time period to help retrain the models for better performance. Other embodiments are described and claimed.

Abstract: Among other things, embodiments of the present disclosure discussed herein help identify trending topics and generate customized data feeds that present trending topics to a user based on information in the user's social network profile. In some embodiments, users may select topics of interest to the user and the system can identity and present trending articles in the selected topic to the user via the user's newsfeed.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to a Key Feature Engine receives a request for a desired number of key features to be identified from a data set in at least a portion of a database. The Key Feature Engine executes instances of multiple types of machine learning data models on the data set to calculate respective regression coefficients, in each machine learning data model instance, for each feature in a plurality of features defined by a plurality of data categories of a social network service. The Key Feature Engine identifies at least one key feature, of one or more instances of the multiple types of machine learning data models, based on a value of a corresponding regression coefficient.

Abstract: A system is configured to determine the impact on ranking of one or more job postings in view of the relevancy of the terms used by the one or more job postings. Using predetermined keywords, the system obtains search results from a variety of sources, and then vectorizes the contents of those search results. Vectorizing may include removing syntactic language and converting the search results to a plain text format. The system further determines relevant terms from the vectorized search results for each of the predetermined keywords, and then computes relevancy values for each of the predetermined keywords using the relevant terms. Through regression modeling, the system determines regression coefficients given the relevancy values and the sources of the search results. The regression coefficients indicate the impact that relevancy of the terms used in the job postings has on the ranking of the job postings.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains training data containing a first set of customer support tickets and a first set of categories assigned to the first set of customer support tickets by customer support agents. Next, the system uses the training data to produce a statistical model for classifying the customer support tickets into the categories. The system then uses the statistical model to classify a second set of customer support tickets into a second set of categories. Finally, the system generates output for routing the second set of customer support tickets to the customer support agents according to the second set of categories.

Abstract: A topical representative assessment system implements techniques for determining entities that are ambassadors for one or more topics. The ambassadors are determined based on content items that they have authored or content items that are otherwise attributed to them. An ambassador may be any type of entity such as a person, a company, or an organization. Machine analytics may be used to determine whether a content item corresponds to a specific topic, determine a sentiment for a content item, analyze feedback for a content item, or any combination of these.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a first configuration for processing a first set of content items from a first data source and a second configuration for processing a second set of content items from a second data source. For each content item in the first set of content items, the system uses mappings from the first configuration to transform original fields from the content item into required fields in a record representing the content item. Next, the system generates, from the required fields, a document key for the content item. The system also performs deduplication of multiple records with the document key and stores a single record with the document key. Finally, the system uses the second configuration to generate, from the second set of content items, a set of records independently of processing the first set of content items.

Abstract: A system and method for identifying trending topics in a document corpus are provided. First, multiple topics are identified, some of which topics may be filtered or removed based on co-occurrence. Then, for each remaining topic, a frequency of the topic in the document corpus is determined, one or more frequencies of the topic in one or more other document corpora are determined, a trending score of the topic is generated based on the determined frequencies. Lastly, the remaining topics are ranked based on the generated trending scores.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of metrics associated with a performance of one or more customer service representatives. Next, the system calculates a productivity key performance indicator (KPI) from the set of metrics, wherein the productivity KPI includes a number of cases (e.g., solved cases, reopened cases, handled cases, and/or routed cases) per queue hour for the one or more customer service representatives. The system then outputs the productivity KPI for use in managing the performance of the one or more customer service representatives.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of key performance indicators (KPI) for one or more customer service representatives, wherein the set of KPIs includes a number of cases (e.g., solved cases, reopened cases, handled cases, and/or routed cases) per queue hour. Next, the system uses the set of KPIs to display a graphical user interface (GUI) comprising a chart of a two-dimensional performance measurement for the one or more customer service representatives. The system then displays, in the chart, a first axis representing a productivity KPI comprising the number of cases per queue hour and a second axis representing an additional KPI from the set of KPIs.

Abstract: In cases where a user of a social network has lost access to one or more email addresses on file with the social network, the social network may confirm an identity of the user before issuing a new password. The social network may confirm the identity of the user by prompting the user to correctly identify pictures of members of the social network that are connected to the user, selecting or receiving a selection of a plurality of trustees (e.g., members of the social network who are connected to the user), prompting the trustees to confirm with the user that the user has lost the access, and receiving notification that at least a specified number of the trustees have confirmed with the user that the user has lost the access. After the social network confirms the identity, the social network may provide a new password to the user.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains validated training data containing a first set of content items and a first set of relevance tags, wherein the first set of relevance tags is used by one or more domain experts to identify the first set of content items as relevant to one or more topics. Next, the system uses the validated training data to produce a statistical model for classifying a relevance of content to the one or more topics. The system then uses the statistical model to generate a second set of relevance tags for a second set of content items. Finally, the system outputs one or more groupings of the second set of content items by the second set of relevance tags to improve understanding of content related to the one or more topics without requiring a user to manually analyze the second set of content items.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains validated training data containing a first set of content items and a first set of classification tags for the first set of content items. Next, the system uses the validated training data to produce a statistical model for classifying content using a set of dimensions represented by the first set of classification tags. The system then uses the statistical model to generate a second set of classification tags for a second set of content items. Finally, the system outputs one or more groupings of the second set of content items by the second set of classification tags to improve understanding of content related to the set of dimensions without requiring a user to manually analyze the second set of content items.

Abstract: In cases where a user of a social network has lost access to one or more email addresses on file with the social network, the social network may confirm an identity of the user before issuing a new password. The social network may confirm the identity of the user by prompting the user to correctly identify pictures of members of the social network that are connected to the user, selecting or receiving a selection of a plurality of trustees (e.g., members of the social network who are connected to the user), prompting the trustees to confirm with the user that the user has lost the access, and receiving notification that at least a specified number of the trustees have confirmed with the user that the user has lost the access. After the social network confirms the identity, the social network may provide a new password to the user.