Adobe, Inc.

Neolane Sas

Tanya Goyal

Balaji Vasan Srinivasan

Cedric Huesler

Payal Bajaj

Sanket Vaibhav Mehta

Niyati Himanshu Chhaya

Sumit Shekhar

Gaurush Hiranandani

Kushal Chawla

Kokil Jaidka

Ankur Jain

Frederic Mary

Projjal Chanda

Jaya Singh

Shiv Kumar Saini

Natwar Modani

Anandhavelu Natarajan

Pranav Ravindra Maneriker

Paridhi Maheshwari

Shriram Venkatesh Shet Revankar

Abhilasha Sancheti

Shriram Revankar

Kundan Krishna

Vineet Sharma

Manas Agarwal

David Nicholas Bieselin

Rajat Chaturvedi

Anish Valliyath Monsy

Sachin Kelkar

Jeenu Grover

Varun Syal

Shubhankar Suman Singh

Nikhil Mohan Nainani

Kartik Sreenivasan

Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitate identification of security policies for documents. In one embodiment, content features are identified from a set of documents having assigned security policies. The content features and corresponding security policies are analyzed to generate a security policy prediction model. Such a security policy prediction model can then be used to identify a security policy relevant to a document.

Tagging documents with security policies

Techniques and systems for determining paywall metrics are described. In an implementation, a candidate paywall metric is created that corresponds to an increased propensity of users to engage in a paid transaction when exposed to a paywall. In this way, providers of digital content may increase the proportion of users that perform a transaction when exposed to the paywall.

Determination of paywall metrics

Techniques are disclosed to assist an author in creating content variations of a given input text to better suit the mood or the affect preferences of the target audience. Affect distribution in the content is utilized to capture these psycholinguistic preferences. According to one embodiment, in a first phase the optimal/idea psycholinguistic preference for text content aimed at a particular audience segment is determined. In a second phase, a given text content is modified to align to a target language distribution, which was determined in the first phase. In one example case, word level replacement, insertions and deletions are executed to generate a modified and coherent version of the input text. The output text thus reflects the psycholinguistic requirements of the audience.

Content optimization for audiences

A framework is provided for constructing enterprise-specific knowledge bases from enterprise-specific data that includes structured and unstructured data. Relationships between entities that match known relationships are identified for each of a plurality of tuples included in the structured data. Where possible, relationships between entities that match known relationships also are identified for tuples included in the unstructured data. If matching relationships between entities that cannot be identified for tuples in the unstructured data, extracted relationships are sequentially clustered to similar relationships and a relationship is assigned to the clustered tuples. An enterprise-specific knowledge graph is constructed from the structured-data-tuples and their identified relationships, the unstructured-data-tuples where the relationships could be mapped to a known relationship and their identified relationships, and the unstructured-data-tuples that could not be mapped to a known relationship and their assigned relationships. The knowledge graph is enriched with any information determined to be missing therefrom.

Constructing enterprise-specific knowledge graphs

Embodiments are disclosed for bundling and arranging online content fragments for presentation based on content-specific metrics and inter-content constraints. For example, a content management application accesses candidate content fragments, a content-specific metric, and an inter-content constraint. The content management application computes minimum and maximum contribution values for the candidate content fragments. The content management application selects, based on the computed minimum and maximum contribution values, a subset of the candidate content fragments. The content management application applies, subject to the inter-content constraint, a bundle-selection function to the selected candidate content fragments and thereby identifies a bundle of online content fragments. The content management application outputs the identified bundle of online content fragments for presentation via an online service.

Bundling online content fragments for presentation based on content-specific metrics and inter-content constraints

Techniques are disclosed for predicting a tone of a text communication using psycholinguistic features of the text communication. In some examples, a method may include generating a feature vector for a text communication using features, including psycholinguistic features, extracted from the text communication, and predicting a tone of the text communication based on the feature vector. The tone is predicted by a trained prediction module that is trained using psycholinguistic features of text communications in a training set used to train the trained prediction module. The predicted tone is at least one of a predicted measure of frustration, a predicted measure of formality, and a predicted measure of politeness.

Prediction of tone of interpersonal text communications

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.

Classifying and ranking changes between document versions

A method for generating predictive insights for authoring messages is provided. The method includes receiving a message to be sent as an input. Key performance indicator (KPI) whose value is to be predicted for the message is identified from the input or marketing tool configuration. A plurality of feature vectors of the message are generated. KPI contributions for the plurality of feature vectors are determined using feature vectors of messages sent in past and tracked KPI values of the messages sent in past. The KPI contribution is a measure of contribution of feature vector to value of the KPI. Value of the KPI for the message is predicted by applying determined KPI contributions to the plurality of feature vectors. Apparatus for substantially performing the method as described herein is also provided.

Generating predictive models for authoring short messages

Content can be displayed in different manners on different devices (e.g., having different display sizes) using different layout templates. The techniques discussed herein automatically select a layout template for the content for a particular display device, and transform the content to that layout template for display. Generally, the content is categorized into multiple different categories, and the layout template is also categorized into the same categories. For each of the categories, a mapping of part of the content to a layout element of the layout template is selected. A content display for the layout template is generated by porting (and possibly transforming) the parts of the content into the mapped-to element (as indicated by the selected edges) of the layout. In one or more embodiments, the content display can then be displayed or communicated to another device for display.

Content to layout template mapping and transformation

Method and apparatus for generating predictive insights for authoring short messages

The collection of social data from social networking services for market research purposes is improved by automating the formulation of a final query rule sets by analyzing relevant keywords captured using a seed query rule set based on a user input. Relevant keywords from social mentions based on a seed query rule set for a brand name and/or product can be extracted to form at least parts of a final query rule set. The relevant keywords can then be disambiguated by using a searchable reference to resolve ambiguities. Any generalities in the relevant keywords can also be resolved by analyzing the co-occurrence of the relevant keywords with relevant keywords from another brand and/or product. The relevant keywords having been disambiguated and having generalities resolved therein, may be used to automatically generate a final query rule set for providing relevant search results based on the user input.

Method to expand seed keywords into a relevant social query

The present disclosure is directed toward systems and method for generating geo-fences having boundaries around geographic regions of interest based on historical activity data of a user application on a plurality of client devices. For example, systems and methods described herein involve tracking activity data to identify instances of an application activity associated with an action to promote and identify locations where users more frequently perform the application activity. In addition, systems and methods described herein involve tracking activity data over time to determine geographic regions of interest at different time periods where users more frequently perform application activities. Further, systems and methods described herein involve generating geo-fences around one or more geographic regions of interest.

Generating data-driven geo-fences

Growing community of inventors

Mumbai, India

Tanya Goyal