Abstract: Particular embodiments generally relate to automatically controlling an item. For example, items may include electronic devices, such as televisions, lights, etc, and/or virtual devices, such as applications, etc. In one embodiment, items may be configured using metatags. When a device is connected for operation, one or more metatags for the device are received. A metatag be used to classify the device. For example, the metatag may indicate uses, locations, connections, etc. The use of device (e.g., pathway, reading, etc.) classifies the item in way it can be used. For example, a user may use a pathway light in different ways, such as the user may turn on all lights with the pathway metatag at night. The location indicates the location of the item, such as in the living room, bedroom, etc. The connections indications a type of item, such as a bedroom light, lamp, TV, etc.

Abstract: A computer-based method and a system for indexing, querying, and ranking documents based on layout are provided. The method includes providing a plurality of documents to computer memory, extracting layout blocks from the provided documents, clustering the layout blocks into a plurality of layout block clusters, computing a representative block for each of the layout block clusters, generating a document index for each provided document based on the layout blocks of the document and the computed representatives blocks, clustering the created document indexes into a plurality of document index clusters, and generating a representative cluster index for each of the document index clusters. The indexes generated, together with the representative blocks and document index clusters, can be stored and used for retrieval of documents responsive to a layout query.

Abstract: Machine readable media, methods, and computing devices are disclosed that mine a dataset using a frequent pattern array. One method of includes building a frequent pattern tree comprising a plurality of nodes to represent frequent transactions of a dataset that comprises one or more items. The method also includes transforming the frequent pattern tree to a frequent pattern array that comprises an item array and a plurality of node arrays, the item array comprising frequent transactions of the dataset and each node array to associate an item of the dataset with one or more frequent transactions of the item array. The method further includes identifying frequent transactions of the dataset based upon the frequent pattern array.

Abstract: Embodiments of the invention may be used to produce a data mining signal by generating hybrid dataset representing data related to tools used during a semiconductor fabrication process. By selectively combining similar processes, the data mining signal strength of each tool used to perform the steps of the fabrication process may be increased. A combined process variable may be used to represent the group of tools and processes, collectively. A set of rules may be composed to determine which processes used in the semiconductor fabrication process should be combined in the hybrid dataset.

Abstract: A method and apparatus for ontology-based classification of media content are provided. With the method and apparatus, initial confidence values of classifiers in a hierarchical classification structure are modified based on relationships between classifiers. A confidence value for a classifier is boosted by a boosting factor based on a correspondence between the confidence value and confidence values of ancestor classifiers in the hierarchical classification structure. A confidence value for a classifier is modified by a confusion factor based on a correspondence between the confidence value of the classifier and the confidence values of mutually exclusive classifiers in the hierarchical classification structure. In this way, a more accurate representation of the actual confidence that media content falls within the classification associated with the classifier is obtained.

Abstract: A system includes a coordinator configured to generate a first offer representing a possible solution to a problem being solved. The coordinator is configured to generate the first offer using a first model. The system also includes multiple cooperators each configured to receive the first offer and to determine if a sub-problem associated with the problem can be solved based on the first offer and using a second model. Each cooperator is also configured to identify an infeasibility and communicate the infeasibility to the coordinator when the sub-problem cannot be solved based on the first offer. The coordinator is further configured to receive the infeasibility, generate a second offer by reducing a deviation between the first offer and a consensus of the cooperators, and provide the second offer to the cooperators. The consensus of the cooperators is based on a level of the first offer that each cooperator can achieve.

Abstract: Embodiments of the invention provide system and methods for new approaches for facilitating the development of and transferring of user thinking and understanding about an arbitrary problem, in some embodiments through automatically creating new interactive forms of thinking and knowledge constructs as enhanced interactive and/or visually appealing presentational and working forms. Some embodiments involve the development of an interactive construct by one or more users for use by one or more other users (as in educational or professional development situations, for example).

Abstract: Disclosed herein is an improved architecture for regular expression pattern matching. Improvements to pattern matching deterministic finite automatons (DFAs) that are described by the inventors include a pipelining strategy that pushes state-dependent feedback to a final pipeline stage to thereby enhance parallelism and throughput, augmented state transitions that track whether a transition is indicative of a pattern match occurring thereby reducing the number of necessary states for the DFA, augmented state transition that track whether a transition is indicative of a restart to the matching process, compression of the DFA's transition table, alphabet encoding for input symbols to equivalence class identifiers, the use of an indirection table to allow for optimized transition table memory, and enhanced scalability to facilitate the ability of the improved DFA to process multiple input symbols per cycle.

Abstract: A method of facilitating the construction, maintenance, and usage of social-trust networks is disclosed. The illustrative embodiment monitors the call processing details of communication events between users of a telecommunications system as the basis for estimating whether or not a relationship exists between the users that can be exploited in a social-trust network. This is possible because the call processing details of communication events between users is an excellent indicator of the nature of the relationship between users. For example, if Alice calls Brian three times a day on average, including nights, weekends, and holidays, and Brian answers Alice's calls quickly and returns her unanswered calls quickly, then it is reasonable to infer that Alice and Brian have a relationship that is substantial enough to be used in a social-trust network.

Abstract: An apparatus and method for measurement, analysis, and optimization of content delivery over a communications network is presented. In one embodiment, the apparatus detects data packets en route over a communications network. The detected data packets are read by the apparatus, combined into application messages, and further combined into user centric events. The events are analyzed to identify metrics and statistics relating to the delivery of content over a communications network and the experience of the end user. The metrics and statistics are saved in a data storage area. When the metrics exceed a configurable threshold, the apparatus provides real-time notification of content delivery problems or end user experience problems. Alternatively, the system can take action to proactively prevent anticipated content delivery problems or end user experience problems.

Abstract: A semantic database transaction monitor is provided that monitors database transactions by taking advantage of database replication technology. The invention receives one or more event streams of transaction data from one or more database replication software agents, originally from transaction logs, and then classifies each transaction, utilizing an inference engine populated with one or more source ontologies and a canonical ontology so that transaction metadata are normalized. The invention then can be utilized to create a data store across multiple databases for reporting and analysis. The invention can also be used to feed normalized database transactions to real-time graphics software for real-time reporting or alerting. Because the process obtains data from event streams, it does not significantly drain the resources of the databases and can provide virtually real-time monitoring. Moreover, it does not require recoding for updates to the databases, but only changes to the ontologies read at runtime.

Abstract: A rule based computerized method is disclosed of developing and/or implementing and/or administering rule based systems such as legislation and/or policy and/or other rule sets, the method including: -developing a computerized database containing a set of rules in accordance with which the rule based system can be developed, written in and delivered; wherein the rules are: -written in natural spoken language to express the individual grammatical units constituting the rules, constrained in being written in accordance with defined constraints to limit the number of logical formats in which the rules can be expressed, and explicit in being written in a manner to avoid implicit meanings; whereby the rules are expressed in a logical format readily understandable to both humans and computers.

Abstract: Automigration mechanisms having fuzzy-logic based automigration control mechanisms for implementing control schemes controlling start, stop and/or bandwidth of the automigration process are provided. The automigration control mechanisms read, into a memory of an automigration controller circuit, configuration parameters characterizing the hardware and software properties of the source storage and target storage, and that of the network connection between them. The mechanisms further derive fuzzy variables from the values of the input variables and of the configuration parameters. The mechanisms further provide a predetermined fuzzy function with the fuzzy variables, where the fuzzy function reflects the exhaustion level of the source executing the fuzzy function yielding a fuzzy result value. The mechanisms apply the fuzzy result value to one of the control schemes, yielding a control result. The mechanisms control the start, stop, and/or bandwidth of the automigration of data by aid of the control result.

Abstract: Embodiments of the disclosure generally relate to systems and methods for authenticating users of an entity system. In embodiments, an authentication platform receives a request for authentication. The authentication platform interacts with one of several authentication modules to authenticate the user. Each authentication module may use different information or procedures to authenticate the user. If authenticated, the user is allowed access to the system. Having access to two or more authentication modules allows the authentication platform to provide automatically a more robust authentication and alleviates the entity system from needing to integrate the several authentication modules.

Abstract: A method for near real time patterns identification, in one example embodiment, comprises receiving a data stream containing information associated with a transaction and participants of the transaction and receiving an Artificial Intelligence (AI) algorithm trained to score data in the data stream. The method may further comprise receiving metadata associated with the historical information, comparing the data stream to the metadata by measuring differences between variables included in the historical metadata and the data stream. The method may further comprise modifying the data stream to suit the AI algorithm when the differences between variables are below predetermined threshold values and retraining the AI algorithm based on the data stream when the differences between the variables are greater than the predetermined threshold values. The method may further comprise feeding the data stream to the AI algorithm to classify the variables in the data stream.

Abstract: Data is organized in a knowledge network by defining a set of nodes, each node comprising data describing knowledge and a task pertinent to the knowledge, and defining relationships between the nodes based on the data.

Abstract: There is provided an information processing apparatus, including a receiving unit that receives a derivational relationship information item designating a document prior to an operation as a parent and a document after the operation as a child, and document attribute of the document after the operation; a derivational relationship storage unit that stores the derivational relationship information item being received; a document attribute storage unit that stores the document attribute being received; and an inference unit that, based on a comparison between document attribute of a document which is a root of a tree structure of derivational relationships of documents represented by derivational relationship information items stored in the derivation storage unit and document attribute of a document included in the derivational relationship information items, infers a document that can be a parent of the root document, the compared document attributes being obtained from the document attribute storage unit.

Abstract: A method of fault diagnostics in a case based reasoning system, wherein said case based reasoning system comprises a plurality of cases, each case having an associated solution and a case weight, said method comprising the steps of: receiving data associated with a fault; determining a case match indicative of the degree of matching between the received data and each of the plurality of cases; providing a solution associated with one of the plurality of cases in dependence on its case match and case weight; receiving an actual solution to the fault; increasing the case weight of the case associated with the provided solution if the actual solution is equal to the provided solution; and adding a new case to the plurality of cases if the actual solution is not equal to the provided solution, wherein the actual solution is associated with the new case.

Abstract: An automatic transfer apparatus for a liquid crystal display device comprising a mounting unit for placing a cassette in which a plurality of substrates are received, a moving unit disposed at a lower surface of the mounting unit and moving within a designated interval or section, and a sensing member mounted in the moving unit for sensing an obstacle, wherein the sensing member for sensing an obstacle at a bottom is disposed at the lower surface of the automatic transfer apparatus so as to enable a previous checking an existence of the obstacle, thereby preventing a structure of the automatic transfer apparatus from being damaged due to the obstacle.

Abstract: The data mining platform comprises a plurality of system modules, each formed from a plurality of components. Each module has an input data component, a data analysis engine for processing the input data, an output data component for outputting the results of the data analysis, and a web server to access and monitor the other modules within the unit and to provide communication to other units. Each module processes a different type of data, for example, a first module processes microarray (gene expression) data while a second module processes biomedical literature on the Internet for information supporting relationships between genes and diseases and gene functionality. In the preferred embodiment, the data analysis engine is a kernel-based learning machine, and in particular, one or more support vector machines (SVMs).