Abstract: A system for identifying abnormal resource usage in a data center is provided. In some embodiments, the system employs a prediction model for each of a plurality of resources and an abnormal resource usage criterion. For each of a plurality of resources of the data center, the system retrieves current resource usage data for a current time and past resource usage data for that resource. The system then extracts features from the past resource usage data for that resource, predicts using the prediction model for that resource usage data for the current time based on the extracted features, and determines an error between the predicted resource usage data and the current resource usage data. After determining the error data for the resources, the system determines whether errors satisfy the abnormal resource usage criterion. If so, the system indicates that an abnormal resource usage has occurred.

Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: This document relates to meeting evaluation. One example determines previous meeting attributes of previous meetings that were attended by a user or to which the user was invited, and obtains implicit feedback about the previous meetings from a device of the user. The example includes training a predictive algorithm to evaluate future meetings for the user using the previous meeting attributes and the implicit feedback about the previous meetings.

Abstract: A computer-implemented method, an apparatus and a computer program for automatically extracting useful information for functional verification. The method comprising performing repeatedly both operating an instruction generator associated with a Design Under Test (DUT), whereby a generated instruction is determined, the generated instruction having one or more instruction attributes; and collecting information relating to the generated instruction. Based on the generated instruction and the collected information, a classification technique is utilized to classify the information based on the instruction attributes.

Abstract: One or more web-behavior-augmented recommendation servers augment catalog interaction data between consumers and a catalog of products with collected online web behavior data associated with individual users. The online web behavior data represents online web behavior of the each consumer outside of the catalog of products and can improve the accuracy of product recommendations, which then be presented to an individual consumer via a computer user interface.

Abstract: The subject disclosure is directed towards monitoring user behavior on a computerized device for any deviation from normal or acceptable behavior that is likely to affect the user's mental state. A prediction model corresponding to features of one or more mental states may be compared with features based upon current user behavior. If the user's current behavior presents a mental state indicative of an uncharacteristic deviation from the normal or acceptable behavior, descriptive data associated with that mental state may be presented to the user in addition to a trusted individual, such as a health care professional.

Abstract: An advanced metering infrastructure comprises intermediate nodes. The intermediate nodes receive data from child nodes and relay a subset of the data that is not according to an expected value. The expected value may be determined based on a forecasting function computed based on past data. The expected value may be a spatial shape in an n-dimension space. A data not within the spatial shape may be considered not in accordance with the expected value. In some case, the spatial shape is defined by a centroid and a radius. The spatial shape may shift over time based on a consumption profile, such as low consumption at noon, and high consumption at evening. The consumption profiles may be determined in a learning phase, as well as shifting of spatial shapes of each group over time.

Abstract: An advanced metering infrastructure comprises intermediate nodes. The intermediate nodes receive data from child nodes and aggregate the data according to groups of child nodes. The aggregation provides for a reduced version of the data. The reduction is performed based on groups determined by clustering. The reduced version of the data comprises data describing a group of measurements over time, such as a centroid in an n-dimension space, number of customers in the group, radius of the group and the like. The centroid may shift over time based on a consumption profile, such as low consumption at noon, and high consumption at evening. The consumption profiles may be determined in a learning phase, as well as shifting of centroids of each group over time.

Abstract: Systems and methods for generating a storage policy for a storage system are provided. The method comprises receiving a target function applicable to a storage system having one or more data storage mediums, wherein the target function represents values for storage parameters associated with productivity or loss tolerance in the storage system; implementing one or more simulation rules according to the received target function; generating one or more storage operation requests to access data on said one or more data storage mediums based on said one or more simulation rules; submitting said one or more storage operation requests to the storage system for processing; analyzing simulation results obtained for the storage system, in response to the storage system processing said one or more storage operation requests; and generating one or more storage policies, by a machine learning entity, in response to analyzing the simulation results.

Abstract: A computer-implemented method, an apparatus and a computer program for automatically extracting useful information for functional verification. The method comprising performing repeatedly both operating an instruction generator associated with a Design Under Test (DUT), whereby a generated instruction is determined, the generated instruction having one or more instruction attributes; and collecting information relating to the generated instruction. Based on the generated instruction and the collected information, a classification technique is utilized to classify the information based on the instruction attributes.

Abstract: A computer-implemented method, an apparatus and a computer program for automatically extracting useful information for functional verification. The method comprising performing repeatedly both operating an instruction generator associated with a Design Under Test (DUT), whereby a generated instruction is determined, the generated instruction having one or more instruction attributes; and collecting information relating to the generated instruction. Based on the generated instruction and the collected information, a classification technique is utilized to classify the information based on the instruction attributes.

Abstract: A novel and useful method for enabling system logs to be effectively and efficiently monitored by ranking the system log messages by their estimated value to administrators and generating a log view that displays the most important messages. The ranking process uses a dataset of system logs from many computer systems to score messages. For better scoring, unsupervised clustering is used to identify sets of systems that behave similarly. The expected distribution of messages in a given system is estimated using the resulting clusters, and log messages are scored using this estimation.

Abstract: Determining a network transmitter that is more likely to cause handoff failures in a telecommunication service based on historical data records. The historical data records may be standard Call Data Records. A probability that a service provided by a first network transmitter will be handoffed to a second network transmitter is determined. An indication that a target network transmitter is overly busy is determined based on the number of failed services for each network transmitter that may handoff a service the target network transmitter and the probability that a service will be handoffed to the target network transmitter. Based on the indication, measures may be taken to increase quality level of the target network transmitter.

Abstract: Device, system, and method of debugging computer programs. For example, a method for debugging computer programs includes: locating a bug in a computer program based on a first score corresponding to a first instrumentation location of the computer program and a second score corresponding to a second instrumentation location of the computer program.

Abstract: The present disclosure relates to web searching, and more particularly to using a user's information, such as the user's geographic location, and social connections, such as geographic location of one or more friends of the user, in web searching, e.g., such as in filtering and/or ranking search results, identifying relevant queries, and/or identifying content, such as news items, for presentation on a web page presented to the user.

Abstract: A system and method including a simulator operating in conjunction with a search-engine, for improving document and site findability. Users input their content (pages or sites) and the simulator will analyze the site in terms of structure and content. It will then give the user a ranked list of suggestions about how the user might improve his/her site's findability. The user will then be able to apply some or all of these suggestions, or any other changes, by virtually modifying the site, and then immediately receive feedback both on how the pages look and a sense of the degree of findability improvement. The interactive process allows users to simulate modifications in their site structure and content in order to improve its findability. When the user completes the modifications and is satisfied with the new findability of his site, the user will be able then to replace his/her current site in the repository with the modified one.

Abstract: A method and system for using social bookmarks wherein a social bookmark is a triplet of the entities of user, document, and tag. The method including: collecting multiple bookmarks; representing the bookmarks as a three-dimensional space or matrix of the number of times a user u, used tag t to bookmark document d; measuring the similarity of two entities of the same type; and using the similarity to weight bookmarks or entities. The weightings may be used to provide a measure of a usefulness of a bookmark for describing a document for retrieval purposes. Two-dimensions of the bookmark space may also be used to predict the third-dimension.

Abstract: a computer-implemented method, an apparatus and a computer program for automatically extracting useful information for functional verification. The method comprising performing repeatedly both operating an instruction generator associated with a Design Under Test (DUT), whereby a generated instruction is determined, the generated instruction having one or more instruction attributes; and collecting information relating to the generated instruction. Based on the generated instruction and the collected information, a classification technique is utilized to classify the information based on the instruction attributes.

Abstract: Determining a network transmitter that is more likely to cause handoff failures in a telecommunication service based on historical data records. The historical data records may be standard Call Data Records. A probability that a service provided by a first network transmitter will be handoffed to a second network transmitter is determined. An indication that a target network transmitter is overly busy is determined based on the number of failed services for each network transmitter that may handoff a service the target network transmitter and the probability that a service will be handoffed to the target network transmitter. Based on the indication, measures may be taken to increase quality level of the target network transmitter.