Abstract: Techniques are disclosed for generating personalized creator recommendations to viewers interested in viewing and interacting with creative works, in the context of a creative platform for publishing and viewing creative works. For each creator, a vector is generated indicating that creator's creative output with respect to a set of one or more creative fields. For each viewer, a vector is generated indicating that viewer's affinity with respect to the same set of creative fields. For a given viewer, a respective creator score is calculated based upon the vector associated with the viewer and the vector associated with that creator (e.g., based on a vector similarity computation). A ranking of each creator for the given viewer is then performed using the respective score, and a set of one or more personalized recommendations is then provided to the viewer based upon the ranking.

Abstract: Techniques for creator aware and diverse recommendations of digital content are described. In one example, a digital medium environment is configured to allocate an amount of content creator access as part of a service. Based on this content creator access, recommendations of content are generated that prioritize content for recommendations based in part the amount of content creator access. Recommendations are generated further based on a representative diversity preference value that captures a level of interest of a consumer in different categories, resulting in a recommendation that is representatively diverse.

Abstract: A method for propagating changes from master content to variant content includes receiving, from a user interface, a modified master text composition that incorporates changes to a master text composition. Each of the master text composition, the modified master text composition, and a variant text composition assigned to the master text composition are divided into text units. A correspondence model is constructed that includes mappings between the text units of the master text composition, the text units of the modified master text composition, and the text units of the variant text composition. Proposed changes to the variant text composition are determined that correspond to the changes to the master text composition based on the mappings. At least one of the proposed changes is integrated into the variant text composition.

Abstract: This disclosure generally covers systems and methods that identify and differentiate types of changes made from one version of a document to another version of the document. In particular, the disclosed systems and methods identify changes between different document versions as factual changes or paraphrasing changes or (in some embodiments) as changes of a more specific revision category. Moreover, in some embodiments, the disclosed systems and methods also generate a comparison of the first and second versions that identifies changes as factual changes or paraphrasing changes or (in some embodiments) as changes of a more specific revision category. The disclosed systems and methods, in some embodiments, further rank sentences that include changes made between different document versions or group similar (or the same) type of changes within a comparison of document versions.

Abstract: Certain embodiments involve selecting metrics that are representative of large metrics datasets and that are usable for efficiently performing anomaly detection. For example, metrics datasets are grouped into clusters based on, for each of the clusters, a similarity of data values in a respective pair of datasets from the metrics datasets. Principal component datasets are determined for the clusters. A principal component dataset for a cluster includes a linear combination of a subset of metrics datasets included in the cluster. Each representative metric is selected based on the metrics dataset having a highest contribution to a principal component dataset in the cluster into which the metrics dataset is grouped. An anomaly detection is executed in a manner that is restricted to a subset of the metrics datasets corresponding to the representative metrics.

Abstract: Certain embodiments involve selecting metrics that are representative of large metrics datasets and that are usable for efficiently performing anomaly detection. For example, a data graph is generated that represents metrics datasets having values for respective metrics. Each node in the graph represents a respective metric, and each edge between nodes represents a respective correlation between a given pair of the metrics datasets. The nodes are grouped into clusters. For each cluster, a principal component dataset is determined and a representative metric is selected using the principal component dataset. A principal component dataset is a linear combination of metrics datasets (or standardized versions of the datasets) represented by a cluster. The representative metric for each cluster is the metric whose dataset was the greatest contributor to the principal component (e.g., the most heavily weighted metric in the linear combination).

Abstract: Systems and methods provide for expanding user-provided content. User-provided input content is received via a user interface. Content that is relevant to the user-provided input content is identified from a repository of previously-generated content. The identified relevant content is divided into content sub-segments. From the content sub-segments, one or more pieces of candidate content are identified based on each content sub-segment's relevance to the received input content. At least one piece of identified candidate content is provided for display. A selection of one or more pieces of identified candidate content is received, such that the selected piece(s) of identified candidate content is appended to the received input content, thereby expanding the user-provided content.

Abstract: Methods and systems are provided herein for summarizing a set of anomalies corresponding to a group of metrics of interest to a monitoring system user. Initially, a set of anomalies corresponding to a group of metrics is identified as having values that are outside of a predetermined range. A correlation value is determined for at least a portion of pairs of anomalies in the set of anomalies. For each anomaly in the set of anomalies, an informativeness value is computed that indicates how informative each anomaly in the set of anomalies is to the monitoring system user. The correlation values and the informativeness values are then used to identify at least one key anomaly and a plurality of non-key anomalies from the set of anomalies. A summary is generated of the identified at least one key anomaly to provide information to the monitoring system user about the set of anomalies for a particular time period.

Abstract: In various implementations, a method includes receiving a set of time series data that corresponds to a metric. A seasonal pattern is extracted from the set of time series data and the extracted seasonal pattern is filtered from the set of time series data. A predictive model is generated from the filtered set of data. The extracted seasonal pattern is filtered from another set of time series data where the second set of time series data corresponds to the metric. The filtered second set of time series data is compared to the predictive model. An alert is generated to a user for a value within the filtered second set of time series data which falls outside of the predictive model.

Abstract: A method for generating summaries includes selecting a first subset of text units of a text composition to incorporate into a first summary of the text composition using a weighting of the text units that indicates for each text unit a relative importance of including the text unit in summaries of the text composition. The weighting of the text units is modified to reduce the relative importance of each text unit in the first subset based on the text unit having been selected for the first subset. A second subset of the text units is selected to incorporate into a second summary of the text composition using the modified weighting of the text units. At least one of the first summary and the second summary are provided to a user device.

Abstract: A method for propagating changes from master content to variant content includes receiving, from a user interface, a modified master text composition that incorporates changes to a master text composition. Each of the master text composition, the modified master text composition, and a variant text composition assigned to the master text composition are divided into text units. A correspondence model is constructed that includes mappings between the text units of the master text composition, the text units of the modified master text composition, and the text units of the variant text composition. Proposed changes to the variant text composition are determined that correspond to the changes to the master text composition based on the mappings. At least one of the proposed changes is integrated into the variant text composition.

Abstract: Certain embodiments involve selecting metrics that are representative of large metrics datasets and that are usable for efficiently performing anomaly detection. For example, a data graph is generated that represents metrics datasets having values for respective metrics. Each node in the graph represents a respective metric, and each edge between nodes represents a respective correlation between a given pair of the metrics datasets. The nodes are grouped into clusters. For each cluster, a principal component dataset is determined and a representative metric is selected using the principal component dataset. A principal component dataset is a linear combination of metrics datasets (or standardized versions of the datasets) represented by a cluster. The representative metric for each cluster is the metric whose dataset was the greatest contributor to the principal component (e.g., the most heavily weighted metric in the linear combination).

Abstract: Multimedia document summarization techniques are described. That is, given a document that includes text and a set of images, various implementations generate a summary by extracting relevant text segments in the document and relevant segments of images with constraints on the amount of text and number/size of images in the summary.

Abstract: A quality metric of a multimedia summary of a multimedia content item is determined based, in part, on semantic similarities of the summary and content item, rather than just on word frequencies. This is accomplished in some embodiments by identifying a semantic meaning of the summary and multimedia content item using vector analysis. The vectors of the summary and the vectors of the multimedia content item are compared to determine semantic similarity. In other examples, the quality metric of the multimedia summary is determined based on, in part, a coherence between an image portion of a summary and a text portion of the summary for determining a quality metric of a multimedia summary.

Abstract: Techniques for assigning a spoken tag in a telecom web platform are provided. The techniques include receiving a spoken tag, comparing the spoken tag to a set of one or more template tags, if the spoken tag is a match to a template tag, assigning the spoken tag and updating frequency of the tag in the set of one or more template tags, and if the spoken tag is not a match to a template tag, assigning the spoken tag and registering the spoken tag as a new tag in the set of one or more template tags.

Abstract: Methods and arrangements for discerning collective interests among communities.

Abstract: A method and system for determining marketing targets is provided. The method includes a customer list comprising a population of potential customers for a product or service. The potential customers are divided into groups of social communities and specified effort criteria associated with the groups of social communities with respect to the product or service are determined. Each specified effort criteria is associated with an associated group of the groups of social communities with respect to the product or service. Specified customers from each group are selected based on each specified effort criteria.

Abstract: Systems and techniques for generating recommendations for items likely to be of interest to a user. Upon an indication that a recommendation may be needed by a user, a plurality of recommendations from different sources are generated and combined. Suitably, each recommendation includes parameters such as accuracy and confidence parameters. Combining the recommendations comprises adjusting the parameters based on a set of rules established by an operator of a system for combining recommendations. The rules may be adjusted by operator inputs through an interface and may be adjusted, if desired, during generation of a recommendation. At least one of the recommendation sources generates recommendations based on social grouping, wherein social groupings are identified based on connections between members and similarity of purchased between members, and wherein a recommendation for a specific user is generated by identifying groups to which the user belongs and items popular within such groups.

Abstract: A method for identifying influence on user interest for products and ability of users and products to be influenced is disclosed. A processor identifies a degree of influence a number of influencers has over user interest for each of a number of products based on a history of user interest of a number of users for the number of products, wherein each influencer in the number of influencers as one of a user in the number of users and a product in the number of products. The processor also identifies a degree of ability of one or more of the number of users and the number of products to be influenced based on the degree of influence of each of the number of influencers and a number of relationships between the one or more of the number of users and the number of products and the number of influencers.

Abstract: Methods and arrangements for constructing and analyzing federated social networks. A first social network with a first plurality of accounts is defined, as well as a second social network with a second plurality of accounts, the second social network being unaffiliated with the second social network. The first and second social networks are federated to determine a union of the first and second social networks and an intersection of the first and second social networks, and second-order connections between one or more of the first plurality of accounts and one or more of the second plurality of accounts are ascertained, the second-order connections including connections outside of the intersection of the first and second social networks and within the union of the first and second social networks.