Abstract: A method for effecting a dialogue with an emulated brain. The method includes the step of receiving a query in the form of a semantic string. The semantic string is then parsed into basic concepts of the query. The basic concepts are then clumped into a clump concept. If the clump concept constitutes part of a dialogue, then the dialogue thread is activated by determining the context of the clump concept and assessing a potential reply from a group of weighted replies, which expected replies are weighted based on the parsed concepts produced in the step of parsing. The heaviest weighted one of the expected replies is selected and the weight of the selected reply after it is selected is downgraded. The selected reply is then generated for output in a sentence structure.

Abstract: A method of predicting earth stresses in response to changes in a hydrocarbon-bearing reservoir within a geomechanical system includes establishing physical boundaries for the geomechanical system, acquiring logging data from wells drilled, and acquiring seismic data for one or more rock layers. The well and seismic data are automatically converted into a three-dimensional digital representation of one or more rock layers within the geomechanical system, thereby creating data points defining a three-dimensional geological structure. The method also includes (a) applying the data points from the geological structure to derive a finite element-based geomechanical model, and (b) initializing a geostatic condition in the geomechanical model, and then running a geomechanics simulation in order to determine changes in earth stresses associated with changes in pore pressure or other reservoir characteristics within the one or more rock layers.

Abstract: A computer program is disclosed including but not limited to instructions to input an initial description of a data format and a batch of data comprising data in a new data format not covered by the initial description, instructions to use the first description to parse the records in the data source, instructions to discard records in the input data that parse successfully, instructions to collect records that fail to parse, instructions to accumulate a quantity, M of records that fail to parse, instructions to return a modified description that extends the initial description to cover the new data, instructions to transform the first description, D into a second description D? to accommodate differences between the input data format and the first description D by introducing options where a piece of data was missing in the input data and introducing unions where a new type of data was found in the input data; and instructions to use a non-incremental format inference system such as LEARNPADS to infer descri

Abstract: The present invention relates to an engineering design method and a system of implementing same. In one embodiment, the method includes a construction process of knowledge components and a design process based on the knowledge components. The knowledge components pack universal modules in the standard forms. Accordingly, the knowledge components are independent from design layouts or design processes of products, and reusable in different projects and platforms. The design process integrates a variety of software platforms via an uniform environment and calls the knowledge components to complete the engineering designs. Further, the design process defines a data relation and an execution relation of the knowledge components and establishes a relationship between the knowledge components without programming. The universal module comprises at least operations, methods, rules and/or flows of an engineering design process and engineering analysis process.

Abstract: A system and method for autonomic problem determination. Events and problems associated with the events are received from a computing resource and are expressed as entries in an event-problem matrix. Expert knowledge is expressed as entries in one or more multi-level structure dictionaries. The system and method enables dynamic interaction between the events in the matrix and the current dictionaries with its entries being updated continuously to maximize correlation among the events and problems. The index of each term in the dictionary is used to calculate the weight of each event in the matrix wherein events having frequent association with a specific problem will be given a higher weight in the matrix. Using singular value decomposition (SVD), the weighted events enable an accelerated and accurate convergence to a set of specific associated problems.

Abstract: A DBMS-based knowledge extension and inference service method recorded on a computer-readable medium includes creating knowledge represented as a triple by using ontology schemas and instances (first step); receiving the knowledge and extending the knowledge by using a knowledge extension rule (second step); and providing an inference service by using the extended knowledge, converting a user query, and processing the query (third step). Further, the third step includes receiving and converting a user query to create the converted query (31st step); determining whether the query is a previously-input query (32nd step); receiving the converted query and the determination result to create a query result (33rd step); receiving the query result of the 33rd step and performing post-processing to create a post-processing result (34th step); and creating a message and protocol suitable for a user interface by using the post-processing result and then presenting an inference result.

Abstract: In embodiments of the present invention improved capabilities are described for helping a user make a decision through the use of a computing facility, where the computing facility may be a machine learning facility. The process may begin with an initial question being received by the computing facility from the user. The user may then be provided with a dialogue consisting of questions from the computing facility and the answers provided by the user. The computing facility may then provide a decision to the user based on the dialog and pertaining to the initial question, such as a recommendation, a diagnosis, a conclusion, advice, and the like. In embodiments, future questions and decisions provided by the computing facility may be improved through feedback provided by the user. In embodiments, the present invention may be utilized in conjunction with a third-party application.

Abstract: The present invention is directed towards methods and computer readable media for annotating and analyzing user reviews on social review systems with inferred analytics. A reference framework is provided by creating context according to previous activity, bias, or background information of a given reviewer. The method of the present invention comprises receiving a first query identifying a given content item, generating a collection of content items based on one or more identical objective attributes associated with the given content item, identifying one or more subjective attributes associated with a given item in the collection of content items, and providing a reference framework to interpret the subjective attributes associated with each item in the collection.

Abstract: Techniques are described herein for analyzing textual responses to questions by evaluating the responses according to varying sets of rules. The text of a response is analyzed against the sets of rules and a series of values are generated as a result of, and based upon, the analysis. These values are calculated to determine a score value for the response, which is compared to a threshold value and/or to the scores of other responses to the same or a different question. The score value of the response is used to determine the likelihood of the response containing useful information in response to the question. Also, based on the third numerical value, the text of the response is displayed on a web page according to a specified format or order.

Abstract: Described herein is a method that includes receiving user history data and generating an indication of quality of a tier assignment used to store searchable digital items in a tiered storage system, wherein the indication is based at least in part upon a subset of the user history data. Also described herein is a system that includes a receiver component that receives user history data. The system further includes a quality indicator component that determines an indication of quality of a tier assignment used to store digital items that are retrievable by way of querying, wherein the quality indicator component generates the indication based at least in part upon a subset of the user history data and the tier assignment indicates where digital items are to be stored in a tiered storage system.

Abstract: Rule selection is enforced on user email inboxes using an inbox monitor and administrative rules at an email server. The inbox monitor includes a first agent for identifying inactive user inboxes from email messages stored at the email database, and a second agent for identifying, from the inactive user inboxes identified by the first agent, user inboxes without appropriate user rules activated. For each user inbox identified by the second agent, administrative rules are applied to the user inbox if the user inbox has been inactive for at least a predetermined period of time. If the user inbox has not been inactive for at least the predetermined period of time, a notification message is sent to a user associated with the user inbox. The notification message informs the user that administrative rules will be applied to the user inbox if appropriate user rules are not activated.

Abstract: Provided is a method comprising delivering a video of an event to a learner that includes a still menu that effectuates and simulates a pause; recording a video of an action by the learner in response to the event; presenting to the learner the video of the action by the learner; presenting to the learner a video showing a preferred action by a master in response to the event; and recording at least one additional action by the learner. Also provided is a method for teaching a learner how to respond to an event comprising allowing the learner to choose among recording an action in response to a video of an event, viewing one or more recorded actions of a master, and comparing the two videos; wherein recording may be chosen before and after either or both viewing and reviewing, and the recordings are viewable as videos on a monitor.

Abstract: In a parallel system, multiple threads operate in parallel to perform network structure learning. A global score cache is partitioned into multiple split score caches, which may in one embodiment include associating a score cache with a node of the structure to be learned. With a split score cache, the learning may be performed in split neighbor scoring loops, with the first loop operating on separate score cache partitions, and warming the score cache partitions for the second loop.

Abstract: In a hierarchical neural network having a module structure, learning necessary for detection of a new feature class is executed by a processing module which has not finished learning yet and includes a plurality of neurons which should learn an unlearned feature class and have an undetermined receptor field structure by presenting a predetermined pattern to a data input layer. Thus, a feature class necessary for subject recognition can be learned automatically and efficiently.

Abstract: The invention, referred to herein as PeaCoCk, uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior. In contrast to traditional purchase-frequency based market basket analysis techniques, such as association rules which mostly generate obvious and spurious associations, PeaCoCk employs information-theoretic notions of consistency and similarity, which allows robust statistical analysis of the true, statistically significant, and logical associations between products. Therefore, PeaCoCk lends itself to reliable, robust predictive analytics based on purchase-behavior.

Abstract: A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.

Abstract: The claimed subject matter provides a system and/or a method that facilitates reducing spam in search results. An interface can obtain web graph information that represents a web of pages. A spam detection component can determines one or more features based at least in part on the web graph information. The one or more features can provide indications that a particular page of the web graph is spam. In addition, a robust rank component is provided that limits amount of contribution a single page can provide to the target page.

Abstract: A system includes: a preference model generating unit that generates a preference model by learning and storing the preference model for a user based on a behavior history that indicates history of behavior of the user; an evaluation list generating unit that calculates probability of a plurality of recommended candidates based on the preference model and generates an evaluation list indicating the probability of the recommended candidates; a default predicting unit that specifies habituation of the user based on the information on the behavior history and calculates a predicted default value of the plurality of recommended candidates based on the habituation; and an evaluated unexpectedness value calculating unit that calculates an evaluated unexpectedness value indicating unexpectedness where the unexpectedness is higher as a difference obtained by subtracting the predicted default value from the probability is larger.

Abstract: A method and system of selecting content from reviews for display are described. A review is identified and partitioned. A subset of the partitions is selected based on predefined criteria. A snippet is generated from the selected partitions. A response that includes the snippet is generated.

Abstract: A computerized data equidistant-mapping method and a computer system using the same are provided. The computerized data equidistant-mapping method is used for mapping M sets of K-dimensional original data into a D-dimensional space in a manner of equidistance. The computerized data equidistant-mapping method includes the following steps. M sets of D-dimensional mapping data each corresponding to each original data respectively and sequentially are generated. An initial mapping data and an initial original data are chosen arbitrarily, wherein the initial mapping data corresponds to the initial original data. The mapping distance between each mapping data and the initial mapping data is computed. The original distance between each original data and the initial original data is computed. Each mapping data is amended according to each mapping distance and each original distance for enabling each mapping data and each original data to have equidistant-mapping relationship gradually.