Oded Vainas

Methods, apparatus, and system to parse an unstructured, natural language input of a user, infer a semantic meaning of an intent of the user, and determine a present or future user state, including a location and a time, in which the intent can be fulfilled.

A modern, personalized, adaptive learning experience may be enabled for distinct groups of students. Content entered in a notebook application or similar platform may be analyzed. Content from a learning object repository may then be selected to be suggested based on comparison with the entered content. A style may also be determined based on one or more of a common attribute of a group of teachers, a common attribute of a group of students, or a rule of an organization. The selected content to… Show more

A modern, personalized, adaptive learning experience may be enabled for distinct groups of students. Content entered in a notebook application or similar platform may be analyzed. Content from a learning object repository may then be selected to be suggested based on comparison with the entered content. A style may also be determined based on one or more of a common attribute of a group of teachers, a common attribute of a group of students, or a rule of an organization. The selected content to be suggested may be automatically customized to conform to the style and a lesson plan, and the customized content may be provided to a client application or another service to be displayed in conformance with the lesson plan to students supporting teachers by freeing teachers' time through optimization of the learning process, creation of easy and simple to use experiences, and actionable analytics and proactive alerts. Show less

Various systems and methods for processing activity data with a knowledge engine to generate actionable insights for a human subject are described. These actionable insights may include identifying a most likely action given a particular state of the human subject, identifying a most likely state in which the human subject performs a particular activity, or identifying anomalies in human activity patterns. In an example, an electronic processing system operates the knowledge engine with… Show more

Various systems and methods for processing activity data with a knowledge engine to generate actionable insights for a human subject are described. These actionable insights may include identifying a most likely action given a particular state of the human subject, identifying a most likely state in which the human subject performs a particular activity, or identifying anomalies in human activity patterns. In an example, an electronic processing system operates the knowledge engine with operations that: identify patterns of activity using clustering of events, identify meaningful patterns of activity from the patterns of activity based on co-occurrence of characteristics for respective events, rank the identified meaningful patterns of activity based on confidence and support of respective patterns to occur for a human subject, and generate a personalization action (such as an action for a software application) based on the ranked, identified meaningful patterns of activity. Show less

System and techniques for search dimensionality expansion are described herein. A history of intelligent agent activity may be received. A search result generated by an external entity may be obtained that includes a set of geographic points of interest (POI). A geographic segment may be retrieved from a geographic segment library when the geographic segment contains a member of the set of POI. Here, the geographic segment defines a geographic area and a dimension set. The search result may be… Show more

System and techniques for search dimensionality expansion are described herein. A history of intelligent agent activity may be received. A search result generated by an external entity may be obtained that includes a set of geographic points of interest (POI). A geographic segment may be retrieved from a geographic segment library when the geographic segment contains a member of the set of POI. Here, the geographic segment defines a geographic area and a dimension set. The search result may be modified to create a modified search result that includes a member of the dimension set. The modified search result may then be transmitted to a user device Show less

Neutropenia is the dose-limiting toxicity of the tri-weekly docetaxel (Taxotere®) schedule. Here, we evaluate in Metastatic Breast Cancer (MBC) patients (N=38) a computerized method for predicting docetaxel-induced neutropenia, and use the model to identify improved docetaxel and Granulocyte Colony Stimulating Factor (G-CSF) regimens. Pharmacokinetics/pharmacodynamics (PK/PD) models were created and simulated concomitantly with a mathematical granulopoiesis model. Individual baseline neutrophil… Show more

Neutropenia is the dose-limiting toxicity of the tri-weekly docetaxel (Taxotere®) schedule. Here, we evaluate in Metastatic Breast Cancer (MBC) patients (N=38) a computerized method for predicting docetaxel-induced neutropenia, and use the model to identify improved docetaxel and Granulocyte Colony Stimulating Factor (G-CSF) regimens. Pharmacokinetics/pharmacodynamics (PK/PD) models were created and simulated concomitantly with a mathematical granulopoiesis model. Individual baseline neutrophil counts and docetaxel schedules served as inputs. Our trial validated the model accuracy in predicting nadir timings (r=0.99), grade 3/4 neutropenia (86% success) and neutrophil profiles (r=0.62). Model was robust to CYP3A-induced variability, except for slightly less accurate grade 3/4 neutropenia predictions. Show less

In implementations, a divergence from a pattern of detected instances of an event is identified, where the event is of a routine of a user. The identified divergence corresponds to an out of routine event. Contextual information is generated corresponding to the identified out of routine event. Furthermore, one or more recommended actions for presenting content to the user are selected based on the contextual information. An indication of the identified out of routine event, the contextual… Show more

In implementations, a divergence from a pattern of detected instances of an event is identified, where the event is of a routine of a user. The identified divergence corresponds to an out of routine event. Contextual information is generated corresponding to the identified out of routine event. Furthermore, one or more recommended actions for presenting content to the user are selected based on the contextual information. An indication of the identified out of routine event, the contextual information, and the one or more recommended actions are provided to a service, which may be an application on a user device. The service can present content to the user based on the identified out of routine event, the generated contextual information corresponding to the identified out of routine event, and the selected one or more recommended actions. The service may follow or disregard any of the selected one or more recommended actions. Show less

One or more techniques and/or systems are provided for providing and/or applying privacy preferences for an entity. A multimedia device, such as a mobile phone, may capture multimedia content associated with an entity (e.g., a photo of a person at a restaurant). The multimedia device may identify a privacy preference for the entity. In an example, the person may be wearing a privacy object that may be recognized as corresponding to the privacy preference. In another example, a device associated… Show more

One or more techniques and/or systems are provided for providing and/or applying privacy preferences for an entity. A multimedia device, such as a mobile phone, may capture multimedia content associated with an entity (e.g., a photo of a person at a restaurant). The multimedia device may identify a privacy preference for the entity. In an example, the person may be wearing a privacy object that may be recognized as corresponding to the privacy preference. In another example, a device associated with the person may emit a signal that may specify a privacy preference for the person and/or may be used by the multimedia device to identify the person (e.g., the identity may be used to query a service to obtain a privacy preference specified for the person). The privacy preference may be applied to the multimedia content (e.g., a no photography privacy preference, a no tagging privacy preference, etc.). Show less