Abstract: Disambiguation in mention detection. The method includes: determining at least one location in a text at which a target surface form in the text appears; obtaining an overall word-bag context of the target surface form in the text, the word-bag context at each of the at least one location including words within a predetermined neighborhood of the location; obtaining an overall resource context of the target surface form in the text, the resource context at each of the at least one location including resources corresponding to a further surface form within a predetermined neighborhood of the location; and determining a similarity between the target surface form and a candidate resource for the target surface form based on the overall word-bag context and the overall resource context. A system for disambiguation in mention detection is also provided.

Abstract: A method comprising using at least one hardware processor for: receiving a topic under consideration (TUC) and a set of claims referring to the TUC; identifying semantic similarity relations between claims of the set of claims; clustering the claims into a plurality of claim clusters based on the identified semantic similarity relations, wherein said claim clusters represent semantically different claims of the set of claims; and generating a list of non-redundant claims comprising said semantically different claims.

Abstract: A method comprising using at least one hardware processor for: identifying relations between pairs of claims of a set of claims; aggregating the claims of the set of claims into a plurality of clusters based on the identified relations; generating a plurality of arguments from the plurality of clusters, wherein each of the arguments is generated from a cluster of the plurality of clusters, and wherein each of the arguments comprises at least one claim of the set of claims, scoring each possible set of a predefined number of arguments of the plurality of arguments, based on a quality of each argument of the predefined number of arguments and on diversity between the predefined number of arguments; and generating a speech, wherein the speech comprises a top scoring possible set of the possible set of the predefined number of arguments.

Abstract: A method comprising using at least one hardware processor for receiving a topic under consideration (TUC); providing the TUC as input to a claim function, wherein the claim function is configured to mine at least one content resource, and applying the claim function to the at least one content resource, to extract claims with respect to the TUC; and providing the TUC as input to a classification function, and applying the classification function to one or more claims of the extracted claims, to output corresponding one or more classification tags, wherein each classification tag is associated with its corresponding claim.

Abstract: A method, apparatus and product useful for classification reliability prediction. The method being a computer-implemented method performed by a processor, the method comprising: obtaining a prediction of a label for a dataset made by a classifier tool, wherein the classifier tool is aimed at predicting the label based on a classification model and in view of a set of features defining the dataset; obtaining a reliability prediction of a reliability label relating to the prediction of the classifier tool based on a reliability classifier tool, wherein the reliability classifier tool is aimed at predicting the reliability label based on a classification model and in view of a second set of features; and outputting to a user the label prediction and an associated reliability prediction.

Abstract: A method, apparatus and product useful for classification reliability prediction. Utilize a separate classifier tool, referred to as a reliability classifier tool or RCT, in order to predict reliability of a prediction made by a classifier tool or CT by introducing additional features that were not used by the classifier tool itself.

Abstract: A computer implemented method, computerized apparatus and computer program product for inconsistency detection between structured and non-structured data. The method comprising: automatically determining, by a computer, inconsistencies between fields in electronics records, the fields comprise at least a structured field and a non-structured field, the fields are designed to be able to include overlapping information in structured and non-structured form; and indicating, by the computer, to a user potential inconsistencies. Optionally, the indication uses a visual cue when displaying the electronic record to the user, wherein the visual cue indicates the fields which are determined to comprise inconsistent content.

Abstract: A method, a system and a computer program product suitable for use in a manufacturing environment comprising a multiplicity of nominally identical independent tools. A computing device generates a multi dimensional array of process trace data derived from at least one of the independent tools, wherein, the array includes data representing a first dimension comprising a list of steps in a manufacturing recipe and data representing a second dimension comprising a list of a set of sensors generating measurements from at least one of the independent tools. The computing device conducts an analysis on at least one preselected subset of the multi dimensional array for the purpose of evaluating at least one operating characteristic of at least one of the independent tools. The computing device presents results of the analysis via a set of hierarchically linked and browseable graphics.

Abstract: A computerized method of generating evidence based case object for a decision support application. The method comprises providing a medical decision point, generating a decision point model mapping between a plurality of patient dependent clinical characteristics and a plurality of treatment options for the medical decision point according to a plurality of guidelines, estimating, using a processor, a plurality of treatment outcomes for each the treatment option, each the treatment outcome being estimated according to an analysis of medical records of a group of patients been at the medical decision point and having a subset of the plurality of patient dependent clinical characteristics selected from a plurality of subsets, and generating evidence based case object which receive patient data having patient dependent clinical characteristics matching one of the plurality of subsets and outputs an estimated prognosis based on a respective treatment outcome from the plurality of treatment outcomes.

Abstract: A computer-implemented method and apparatus for receiving a multiplicity of medical cases associated with a disease, each of the multiplicity of medical cases comprising medical features and assigned treatment, wherein the medical cases are divided into two or more groups such that each of groups is associated with a treatment assigned to medical cases classified into the group; and using the multiplicity of medical cases as divided into the two or more groups, to determine information.

Abstract: A method, apparatus and product useful for classification reliability prediction. The method being a computer-implemented method performed by a processor, the method comprising: obtaining a prediction of a label for a dataset made by a classifier tool, wherein the classifier tool is aimed at predicting the label based on a classification model and in view of a set of features defining the dataset; obtaining a reliability prediction of a reliability label relating to the prediction of the classifier tool based on a reliability classifier tool, wherein the reliability classifier tool is aimed at predicting the reliability label based on a classification model and in view of a second set of features; and outputting to a user the label prediction and an associated reliability prediction.

Abstract: A computer-implemented method and apparatus, the apparatus comprising an information receiving component, a text presentation component for presenting at least a first part of the information on a first pane as text; a form presentation component for presenting at least a second part of the information as a structured form comprising one or more fields on a second pane; and an update component for updating information displayed in the first pane or the second pane in response to changes entered to information displayed in the second pane or in the first pane, respectively.

Abstract: Method, system, and computer program product for visualization of patient treatments are provided. The method includes: selecting a patient; retrieving data records of patients with similar conditions requiring treatment to the selected patient; and building a tree structure for display with nodes of treatment options and a temporal axis showing treatment results of the similar patients. The tree structure includes representing side effects of a treatment option at a node including a visualization of the strength of the side effect. The tree structure also includes providing edges between the nodes representing a length to progression of the condition requiring treatment.

Abstract: A method and system for evaluating a performance of a semiconductor manufacturing tool while manufacturing microelectronic devices are disclosed. At least one report is generated based on executions of at least one statistical test. The report includes at least one heat map having rows that correspond to sensors, columns that correspond to trace data obtained during recipe steps, and cells at the intersection of the rows and the columns. At least one sensor in the tool obtains trace data of a recipe step while manufacturing at least one microelectronic device. A computing device analyzes the obtained trace data to determine a level of operational significance found in the data and assigns a score to the trace data that indicates a level of operational significance. Then, the computing device places the score in a corresponding cell of the heat map. A user uses the cell for evaluating the tool performance.

Abstract: Consumption levels are monitored over a period of time and analyzed. In response to a determination that a monitored consumption level is above a threshold that is defined based on consumption levels of an associated reference group, a notification may be provided. A plurality of notifications may be prioritizing based on a priority index. The plurality of notifications or portions thereof may be provided based on the determined priorities. The priority may take into account parameters such as for example cost of consumption, variance in respect to past consumption levels, variance in respect to the reference group and the like.

Abstract: A method and system for evaluating a performance of a semiconductor manufacturing tool while manufacturing microelectronic devices are disclosed. At least one report is generated based on executions of at least one statistical test. The report includes at least one heat map having rows that correspond to sensors, columns that correspond to trace data obtained during recipe steps, and cells at the intersection of the rows and the columns. At least one sensor in the tool obtains trace data of a recipe step while manufacturing at least one microelectronic device. A computing device analyzes the obtained trace data to determine a level of operational significance found in the data and assigns a score to the trace data that indicates a level of operational significance. Then, the computing device places the score in a corresponding cell of the heat map. A user uses the cell for evaluating the tool performance.

Abstract: A first total number of nodes in a first node set directly linked to a first node can be computed. A second total number of nodes in a second node set directly linked to a second node can be computed. A shared total number of nodes in a union of the first node set and the second node set can be computed. A mutual information metric can then be computed from the first total, the second total, and the shared total. A decision as to whether a new connection should be added between the first node and the second node, which were not previously directly connected, can be determined from the value of mutual information metric.

Abstract: A discriminative feature selection method for selecting a set of features from a set of training data sequences is described. The training data sequences are generated by at least two data sources, and each data sequence consists of a sequence of data symbols taken from an alphabet. The method is performed by first building a suffix tree from the training data. The suffix tree contains only suffixes of the data sequences having an empirical probability of occurrence greater than a first predetermined threshold, from at least one of the sources. Next the suffix tree is pruned of all suffixes for which there exists in the suffix tree a shorter suffix having equivalent predictive capability, for all of the data sources.