Abstract: Emails or other communications are labeled with a category label such as “spam” or “good” without using confidential or Personally Identifiable Information (PII). The category label is based on features of the emails such as metadata that do not contain PII. Graphs of inferred relationships between email features and category labels are used to assign labels to emails and to features of the emails. The labeled emails are used as a training dataset for training a machine learning model (“MLM”). The MLM model identifies unwanted emails such as spam, bulk email, phishing email, and emails that contain malware.

Abstract: Emails or other communications are labeled with a category label such as “spam” or “good” without using confidential or Personally Identifiable Information (PII). The category label is based on features of the emails such as metadata that do not contain PII. Graphs of inferred relationships between email features and category labels are used to assign labels to emails and to features of the emails. The labeled emails are used as a training dataset for training a machine learning model (“MLM”). The MLM model identifies unwanted emails such as spam, bulk email, phishing email, and emails that contain malware.

Abstract: Emails or other communications are labeled with a category label such as “spam” or “good” without using confidential or Personally Identifiable Information (PII). The category label is based on features of the emails such as metadata that do not contain PII. Graphs of inferred relationships between email features and category labels are used to assign labels to emails and to features of the emails. The labeled emails are used as a training dataset for training a machine learning model (“MLM”). The MLM model identifies unwanted emails such as spam, bulk email, phishing email, and emails that contain malware.

Abstract: In one embodiment, a method includes receiving digital media content files. The digital media content has at least one property associated with it. Topically related segments are determined from received content in accordance with one or more property. Topic clusters are generated based on similarities between segments. Topic clusters are compared and clustered from multiple files of the plurality into cluster groups in accordance with a comparison. Cluster groups are associatively stored in a data storage. A search for topic clusters relevant to a particular need is made, and a series of related segments associated with the search are generated for serial display.

Abstract: In one embodiment, a processor can receive data representing a view reflected by a mirror of a plurality of mirrors. The plurality of mirrors may be configured in a space to reflect a plurality of views of structures in the space. The mirror of the plurality of mirrors may include a uniquely identifiable feature distinguishable from other objects in the space. The processor can identify the mirror of the plurality of mirrors according to the uniquely identifiable feature. The processor can also determine an attribute of the structures according to the identified mirror and the data representing the view reflected by the mirror.

Abstract: Videoconferencing may be provided. A participant may be identified from audio information and in video information. From the video information, a plurality of images may be captured of the participant identified in the video information. A unique identifier may be associated with the captured plurality of images. The unique identifier may correspond to the participant identified from the audio information. The captured plurality of images and the associated unique identifier may be saved in a database.

Abstract: In particular embodiments, a method includes, from an indexer in a sensor network, accessing a set of sensor data that includes sensor data aggregated together from sensors in the sensor network, one or more time stamps for the sensor data, and metadata for the sensor data identifying one or more pre-determined attributes of the sensor data. The method includes, at the indexer, generating an index of the set of sensor data according to a multi-dimensional array configured for querying of the set of sensor data along with a plurality of other sets of sensor data. One or more first ones of the dimensions of the multi-dimensional array include time, and one or more second ones of the dimensions of the multi-dimensional array include one or more of the pre-determined sensor-data attributes. The method includes, from the indexer, communicating the index of the set of sensor data for use in responding to one or more queries of the set of sensor data along with a plurality of other sets of sensor data.

Abstract: In particular embodiments, a method includes accessing sensor data from sensor nodes in a sensor network and aggregating the sensor data for communication to an indexer in the sensor network. The aggregation of the sensor data includes deduplicating the sensor data; validating the sensor data; formatting the sensor; generating metadata for the sensor data; and time-stamping the sensor data. The metadata identifies one or more pre-determined attributes of the sensor data. The method also includes communicating the aggregated sensor data to the indexer in the sensor network. The indexer is configured to index the aggregated sensor data according to a multi-dimensional array for querying of the aggregated sensor data along with other aggregated sensor data. One or more first ones of the dimensions of the multi-dimensional array include time and one or more second ones of the dimensions of the multi-dimensional include one or more of the pre-determined sensor-data attributes.

Abstract: A system for automatic visitor monitoring comprises one or more sensors and a processor. The one or more sensors can be configured to automatically generate electronic sensor data regarding visitors at a venue. The processor can be configured to process the electronic sensor data to identify one or more visitors. The processor can also be configured to identify one or more characteristics of the behavior of the one or more visitors or devices carried by said visitors. Even further, the processor can be configured to determine if two or more visitors are part of a single visitor group unit.

Abstract: In particular embodiments, a method includes receiving a query for particular sensor data among multiple sensor data from multiple sensors. The plurality of sensor data has been indexed according to a multi-dimensional array. One or more first ones of the dimensions include time, and one or more second ones of the dimensions include one or more pre-determined sensor-data attributes. The method includes translating the query to correspond to the indexing of the plurality of sensor data. The translated query includes one or more values for one or more of the dimensions of the multi-dimensional array. The method includes communicating the translated query to search among the plurality of sensor data according to its indexing to identify the particular sensor data.

Abstract: In one embodiment, a method includes obtaining media that includes a video stream and an audio stream. The method also includes detecting a number of faces visible in the video stream, and performing a speaker segmentation on the media. Performing the speaker segmentation on the media includes utilizing the number of faces visible in the video stream to augment the speaker segmentation.

Abstract: In one embodiment, a method includes receiving digital media content files. The digital media content has at least one property associated with it. Topically related segments are determined from received content in accordance with one or more property. Topic clusters are generated based on similarities between segments. Topic clusters are compared and clustered from multiple files of the plurality into cluster groups in accordance with a comparison. Cluster groups are associatively stored in a data storage. A search for topic clusters relevant to a particular need is made, and a series of related segments associated with the search are generated for serial display.

Abstract: In one embodiment, a processor can receive data representing a view reflected by a mirror of a plurality of mirrors. The plurality of mirrors may be configured in a space to reflect a plurality of views of structures in the space. The mirror of the plurality of mirrors may include a uniquely identifiable feature distinguishable from other objects in the space. The processor can identify the mirror of the plurality of mirrors according to the uniquely identifiable feature. The processor can also determine an attribute of the structures according to the identified mirror and the data representing the view reflected by the mirror.

Abstract: In one embodiment, a method includes obtaining media that includes a video stream and an audio stream. The method also includes detecting a number of faces visible in the video stream, and performing a speaker segmentation on the media. Performing the speaker segmentation on the media includes utilizing the number of faces visible in the video stream to augment the speaker segmentation.

Abstract: Videoconferencing may be provided. A participant may be identified from audio information and in video information. From the video information, a plurality of images may be captured of the participant identified in the video information. A unique identifier may be associated with the captured plurality of images. The unique identifier may correspond to the participant identified from the audio information. The captured plurality of images and the associated unique identifier may be saved in a database.

Abstract: A memory device and related techniques are provided to modify data stored in the memory device without the need to send the data to an external device. A command is received at the memory device to modify data stored at a memory location in a memory array of the memory device. The command includes a value to be used for modifying the data. The memory device reads data from the memory location. The data read from the memory location is modified with modify circuit in the memory device based on the value obtained form the command to produce results data. The results data produced by the modify circuit is written back to the memory location. Since the memory device does not need to send the data read from the memory array off-chip to another device, referred to herein as a host device, to update the data, the input/output bandwidth of the bandwidth is substantially reduced, allowing for lower power memory device operation and reduced latency.

Abstract: In one embodiment, a method includes receiving a summary of statistics concerning a sensor node in a sensor network that comprises a plurality of sensor nodes, the statistics having been generated based on one or more of sensor data from a sensor at the sensor node, communication to the sensor node from one or more other sensor nodes in the sensor network, or communication from the sensor node; analyzing the summary; and applying based on the analysis one or more predetermined polices to one or more of the sensor nodes or the sensor network.

Abstract: In one embodiment, a method includes generating a set of statistics concerning a sensor node in a sensor network based on one or more of sensor data from a sensor at the sensor node, communication to the sensor node from one or more other sensor nodes in the sensor network, or communication from the sensor node; determining based on a subset of the set of statistics whether a predetermined anomalous event correlated with the subset has occurred; and, if the predetermined anomalous event has occurred, generating a summary of the subset and communicating it to a police node in the sensor network.

Abstract: In one embodiment, a method includes accessing first information identifying a sensor-data set that includes sensor-data from multiple sensor-data streams from multiple sensors over a period of time, with the sensor data from the sensor-data streams having been combined with each other based on a relationship of the sensor data to a sensor subject; accessing second information identifying one or more offers to purchase the sensor-data set; and matching one of the offers with the sensor-data set to facilitate a purchase of the sensor-data set based at least on the one of the offers matched to the sensor-data set.

Abstract: In one embodiment, a method includes accessing first information identifying a sensor-data set that includes sensor-data from multiple sensor-data streams from multiple sensors over a period of time, with the sensor data from the sensor-data streams having been combined with each other based on a relationship of the sensor data to a sensor subject; accessing second information identifying one or more offers to purchase the sensor-data set; and matching one of the offers with the sensor-data set to facilitate a purchase of the sensor-data set based at least on the one of the offers matched to the sensor-data set.