Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electric posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.

Abstract: A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.

Abstract: A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.

Abstract: An online social networking system collects data relating to members, and clusters the data into a plurality of clusters. The system identifies anomalous activity by a member in a cluster, and predicts an update to a profile of the member based on the identified anomalous activity of the member. The system presents to the member a proposed update to the profile of the member based on the prediction, receives input from the member in response to the proposed update, and updates the profile of the member based on the input received from the member.

Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electric posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: Examples disclosed herein are relevant to garbage collection for data structures, such as hash tables. The data structure can store garbage collection values for use during a garbage collection process. The garbage collection values can have a value indicating the occurrence of a poisoned status. Disclosed configurations can be suited for use in high-performance computing applications.

Abstract: A node management protocol is disclosed herein. The protocol can be used for task distribution in multi-node systems. The node management protocol can implement a cooperation-based task distribution algorithm that does not rely on consensus. When a task is ingested into a cluster of nodes, the nodes can compete to handle the task. A transport layer helps coordinate among nodes and facilitates the handling of work. A session expiry protocol handles node failures with the remaining nodes reassigning work.

Abstract: Examples disclosed herein are relevant to configurations of hash tables. An example hash table includes is configured to be placed into a contiguous block of shared memory and be used across multiple processes. The hash table can include a memory layout having two logical tables: a metadata table and a storage array. In addition, a storage bitmap can be used to determine available memory locations in the storage array. Disclosed configurations can be suited for use in high-performance computing applications.

Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electronic posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electronic posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: An online social networking system collects data relating to members, and clusters the data into a plurality of clusters. The system identifies anomalous activity by a member in a cluster, and predicts an update to a profile of the member based on the identified anomalous activity of the member. The system presents to the member a proposed update to the profile of the member based on the prediction, receives input from the member in response to the proposed update, and updates the profile of the member based on the input received from the member.

Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electronic posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electronic posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: A computer system receives a data stream with a plurality of packets. In response to receiving the data stream with the plurality of packets, the computer system distributes individual packets of the plurality of packets to the inputs of each of a plurality of processing nodes. Each respective processing node has a local queue storing a respective number of packets to be processed by the respective processing node. Distributing a respective packet of the plurality of packets to the inputs of each of the plurality of processing nodes includes delaying sending the respective packet to each of the plurality of processing nodes by a delay time that is a non-linear function of an average number of packets in the local queues of the respective processing nodes.

Abstract: A computer system performs a continuous monitoring process for a data stream that includes a plurality of packets. The continuous monitoring process includes, without user intervention, distributing the plurality of packets to an input of a filter. The filter is configured to accept individual packets according to a filter graph definition. The process further includes identifying packets as accepted according to the filter graph definition. While performing the continuous monitoring process, the system repeatedly inserts instances of a debugging packet into the data stream for distribution to the input of the filter. The debugging packet is configured to be accepted by the filter. For each debugging packet, the system determines whether the debugging packet was accepted by the filter. When the respective debugging packet was not accepted by the filter, the system reports a problem with performance of the continuous monitoring process for the data stream.

Abstract: A method is provided for automatically discovering topics in electronic posts, such as social media posts. The method includes receiving a corpus that includes a plurality of electronic posts. The method further includes identifying a plurality of candidate terms within the corpus and selecting, as a trimmed lexicon, a subset of the plurality of candidate terms using predefined criteria. The method further includes clustering at least a subset of the plurality of electronic posts according to a plurality of clusters using the lexicon to produce a plurality of statistical topic models. The method further includes storing information corresponding to the statistical topic models.

Abstract: A computer system performs a continuous monitoring process for a data stream that includes a plurality of packets. The continuous monitoring process includes, without user intervention, distributing the plurality of packets to an input of a filter. The filter is configured to accept individual packets according to a filter graph definition. The process further includes identifying packets as accepted according to the filter graph definition. While performing the continuous monitoring process, the system repeatedly inserts instances of a debugging packet into the data stream for distribution to the input of the filter. The debugging packet is configured to be accepted by the filter. For each debugging packet, the system determines whether the debugging packet was accepted by the filter. When the respective debugging packet was not accepted by the filter, the system reports a problem with performance of the continuous monitoring process for the data stream.

Abstract: A computer system identifies high-value information in data streams. The computer system receives a filter graph definition. The filter graph definition includes a plurality of filter nodes, each filter node including one or more filters that accept or reject packets. Each respective filter is categorized by a number of operations, and the one or more filters are arranged in a general graph. The computer system performs one or more optimization operations, including: determining if a closed circuit exists within the graph, and when the closed circuit exists within the graph, removing the closed circuit; reordering the filters based at least in part on the number of operations; and parallelizing the general graph such that the one or more filters are configured to be executed on one or more processors.

Abstract: A computer system identifies high-value information in data streams. The computer system receives a plurality of filter graph definitions. Each of the filter graph definitions includes a plurality of filter nodes arranged in a two-dimensional graph by a plurality of graph edges. Each filter node is configured to accept or reject individual packets in a data stream based on content and/or metadata information associated with the individual packet. The system prepares the filter graph for execution. In response to receiving a data stream with a plurality of packets, the system distributes the packets to inputs of each of the executable filter graph definitions. The system identifies, using the executable filter graph definitions, packets with high-value information based on parallel execution of the filter nodes included in the respective filter graph definition.