Abstract: A system includes a memory operable to store one or more classification rules. The system also includes a processor communicatively coupled to the memory. The processor is operable to retrieve one or more data elements from a data source. The processor is further operable to identify a structured data element among the one or more data elements. The processor is further operable to parse the structured data element using one or more filter processes to produce a plurality of tokens. The processor is further operable to classify the plurality of tokens based at least in part on the one or more classification rules and an ontology, which includes a plurality of concepts and a plurality of relationships between the concepts. The processor is further operable to generate a knowledge assertion, which includes the plurality of classified tokens and one or more relationships between the classified tokens.

Abstract: To implement open information extraction, a new extraction paradigm has been developed in which a system makes a single data-driven pass over a corpus of text, extracting a large set of relational tuples without requiring any human input. Using training data, a Self-Supervised Learner employs a parser and heuristics to determine criteria that will be used by an extraction classifier (or other ranking model) for evaluating the trustworthiness of candidate tuples that have been extracted from the corpus of text, by applying heuristics to the corpus of text. The classifier retains tuples with a sufficiently high probability of being trustworthy. A redundancy-based assessor assigns a probability to each retained tuple to indicate a likelihood that the retained tuple is an actual instance of a relationship between a plurality of objects comprising the retained tuple. The retained tuples comprise an extraction graph that can be queried for information.

Abstract: Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyzes on such extracted content and present graphical representations of such analyzes on a display of a client device.

Abstract: There is provided an information processing apparatus including an information amount gain calculation unit that, on the assumption that a factor that could cause a state transition in a state transition model occurs and the state transition takes place as a result of an occurrence of the factor, determines an information amount gain, which is an information amount obtained by causing the factor to occur regarding a causal relationship between the factor and the state transition and observing a result thereof, an evaluation value calculation unit that determines an evaluation value to evaluate effectiveness of causing each of the factors to occur based on the information amount gain to acquire the causal relationship between the factor and the state transition, and a decision unit that decides the factor to be occurred based on the evaluation value.

Abstract: Systems and methods for classifying a set of documents are provided. In some aspects, a method includes receiving a subset of the set of documents. The method also includes automatically determining at least one classification rule for the subset of documents based on the documents in the subset. At least a true-positive threshold proportion of documents in the subset of documents follows the at least one classification rule. At most a false-positive threshold proportion of documents in the set of documents and not in the subset of documents follow the at least one classification rule. The method also includes storing the at least one classification rule in association with the subset of documents.

Abstract: The method for implementing meta rules on an executable rule engine includes parsing a business rule as input into a meta rule on a rule engine. The meta rule includes a first expression defining one or more style conditions for business rules. The business rule includes a second expression defining logic for an entity. The method includes determining that a business rule violates a style condition defined by the meta rule. The business rule and the meta rule conform to a common business rule syntax. The method includes generating a notification in response to determining that the business rule violates the style condition of the meta rule.

Abstract: Predictions of a given predictive model may be improved using aggregate information. A plurality of targets to predict in a given domain may be identified, and may be predicted based on raw data set. Aggregate information associated with the plurality of targets is received, the aggregate information including estimated or actual values at a coarser level of the plurality of targets, and based on the aggregate information, the predicted target values may be improved in prediction accuracy.

Abstract: Methods, systems, and apparatus, including computer programs encoded on one or more computer storage devices, for training predictive models. Multiple training data records are received that each include an input data portion and an output data portion. A training data type is determined that corresponds to the training data. For example, a training data type can be determined by inputting the output data portions into one or more trained predictive classifiers. In other example, the training data type can be determined by comparison of the output data portions to data formats. Based on the determined training data type, a set of training functions are identified that are compatible with the training data of the determined training data type. The training data and the identified set of training functions are used to train multiple predictive models.

Abstract: There is provided a ubiquitous monitoring system comprising a plurality of sensing nodes; one or more monitoring agents receiving and transmitting sensing data of the sensing nodes; a monitoring module receiving the sensing data from the one or more monitoring agents and managing the sensing data for each type and time; an analysis module deducing one of function information, performance information, and status information for each of smart objects in a ubiquitous space, based on the sensing data, deducing one of function information, performance information, and status information of a ubiquitous service performed by coupled smart objects, and transmitting a result of deduction; and a monitoring viewer displaying the result of deduction to a user.

Abstract: A method for profiling network traffic of a network. The method includes identifying a training set having captured payloads corresponding to a set of flows associated with a network application, determining a set of signature terms from the training set, representing a portion of the captured payloads as regular expressions, representing a regular expression as a path in a modified term transition state machine (MTTSM) including states coupled by at least a link that is assigned a signature term, and analyzing, based on the MTTSM, a flow separate from the set of flows and associated with a server in the network to determine the server as executing the network application.

Abstract: Embodiments of the invention relate to systems, methods, and computer program products for evaluating and selecting technology. Specifically, present embodiments provide for assessing the relative importance of various capabilities and constraints to determine weighting factors and applying the weighting factors to potential technology solutions rated in terms of the applicability of the capabilities and constraints. The result is a capability fit score and a constraint fit score for each potential technology solution, which can be combined to form an overall technology fit score for each potential technology solution. Thus, present embodiments assess capabilities and constraints of various potential technology solutions and balance the capabilities and constraints to result in a quantitatively measurement of which technology solution is the best fit for the project at hand.

Abstract: An information processing device includes: a candidate generating unit employing a user evaluation matrix of evaluation values indicating evaluations as to multiple contents for multiple users to generate multiple estimated expression candidates which are candidates of an estimated expression employed for estimating an evaluation as to a content of a user; an estimation results computing unit computing the user evaluation matrix by the respective estimated expression candidates to generate an estimation result configured of a predictive evaluation value which is the estimation value of an evaluation value; and an estimated expression selecting unit, in a case where several estimation results are employed, and several estimated expression candidates are employed as estimated expressions, obtaining linear combination coefficients employed for obtaining a final estimation result, and selecting an estimated expression candidate and linear combination coefficient having the highest evaluation as the estimated expr

Abstract: A surveillance system implements an architecture and process to support real-time abnormal behavior assessment operations in a distributed scalable sensor network. An automated behavior model builder generates behavior models from sensor data. A plurality of abnormal behavior scoring engines operating concurrently to generate abnormal behavior assessment models by scoring the behavior models. An execution performance manager performs fast switching of behavior models for the abnormal behavior scoring engines. The execution performance manager performs detection of abnormal behavior score distribution characteristic deviation by comparing a current abnormal behavior assessment model to a pre-recorded abnormal behavior assessment model. The execution performance manager selects a pre-recorded behavior model for the abnormal behavior scoring engines when the deviation exceeds a predetermined threshold.

Abstract: For a software component to be installed on a target computer system a product dependency graph is determined which identifies additional software components required by the to-be-installed software component as prerequisite or corequisite software components. For each of these software components a corresponding installation facility is determined. Then a process model is generated being executable by a Workflow Management System (WFMS). The WFMS process model comprises a directed graph of activities, wherein each software component of the product dependency graph is associated with an activity such that when the activity is executed the installation facility corresponding to each of the software components is performed. Moreover, the WFMS process model is generated in a way that the sequence of activities in the directed graph is not violating the dependencies of the software components in the product dependency graph. Finally the WFMS process model is inserted in the WFMS as the provisioning process.

Abstract: A script generating system includes a data dictionary adapted to include table structure data. A database management system runs a script generator, which includes a plurality of user defined templates. Activation of the script generator utilizes built-in macros within the database management system and extracts the table structure data. Responsively, one of the templates manipulates the table structure data to generate a script.

Abstract: Shadow paging is a technique used to achieve atomic and durable transactions, and provides the ability to manipulate pages in a database. During a transaction, the pages affected by the transaction are copied from the database file into a workspace, such as volatile memory, and modified in that workspace. When a transaction is committed, all of the pages that were modified by the transaction are written from the workspace to unused pages in the database file. During execution of the transaction, the state of the database exposed to the user is that in which the database existed prior to the transaction, since the database file still contains the original versions of the modified pages, as they existed before being copied into the workspace. If a user accesses the database before the transaction is complete, or upon recovery of a failure, it will appear as though the transaction has not occurred.

Abstract: A method and system to minimize to redundancy in testing a new software system by utilizing a knowledge base is provided. The knowledge base may be represented in a form of a decision tree including leaf nodes which store previously tested optimal configurations. When the knowledge base does not contain an optimal configuration for the new software, an optimal solution for the new software system may be determined by adding a further decision tree branch to the initial decision tree. A desirable tree branch may be selected from a table including a predetermined set of desirable tree branches for each category of software. As a result, the number of solutions to be tested on the input software may be limited and cost and effort to run redundant tests on a software system may be reduced.

Abstract: The present invention provides a change log handler than can accommodate a change log having an entry that includes more than one modification operation or multi-valued attributes. The change log handler typically includes a change parser for parsing change attributes corresponding to the change log that identify changes to the first data source. Such changes can include a plurality of modification operations as reflected in a single entry of the change log. The change log handler also includes a change reflector for applying the changes to a second data source.

Abstract: A method for providing data collection from a client at a data collection mechanism, the method includes collecting from a client a first portion of data at a first data collection mechanism using at least a portion of a first script comprising one or more queries for information to the client. The method also includes associating the client with a second data collection mechanism based at least in part on an event associated with the client's interaction with the first data collection mechanism. After associating the client with the second data collection mechanism, collecting from the client a second portion of data using a second script, wherein the second script comprises at least one query for information not yet presented to the client by the first script.

Abstract: A logical data model (LDM) design methodology that utilizes common or shared subject areas, developed for applications across two or more industries, in the design and construction of data warehouse solutions and logical data models for specific customers. The development and use of shared subject areas provides for more effective new LDM development through re-use of common elements and quicker deployment of horizontal applications on all industries.