Abstract: Aspects of the present invention disclose a method for managing the control policies associated with processing of a set of resources by a distribution system. The method includes one or more computer processors determining information associated with a configuration of a distribution system. The method further includes determining information related to a set of resource to process utilizing the distribution system. The method further includes determining respective values for a plurality of parameters related to processing the set of resources utilizing the distribution system. The method further includes selecting an initial set of control policies; The method further includes updating the initial set of control policies. The method further includes instructing the distribution system to process the set of resources utilizing the updated set of control policies.

Abstract: An example system includes a processor to receive parameters of a fluid network control system. The processor can formulate an optimal control problem as proportions of server effort. The processor can also solve the optimal control problem using a robust counterpart of a separated continuous linear programming (SCLP). The processor can further adjust a parameter of the fluid network control system based on the optimal solution.

Abstract: Aspects of the present invention disclose a method for managing the control policies associated with processing of a set of resources by a distribution system. The method includes one or more computer processors determining information associated with a configuration of a distribution system. The method further includes determining information related to a set of resource to process utilizing the distribution system. The method further includes determining respective values for a plurality of parameters related to processing the set of resources utilizing the distribution system. The method further includes selecting an initial set of control policies; The method further includes updating the initial set of control policies. The method further includes instructing the distribution system to process the set of resources utilizing the updated set of control policies.

Abstract: An example system includes a processor to receive parameters of a fluid network control system. The processor can formulate an optimal control problem as proportions of server effort. The processor can also solve the optimal control problem using a robust counterpart of a separated continuous linear programming (SCLP). The processor can further adjust a parameter of the fluid network control system based on the optimal solution.

Abstract: A method, computer system, and computer program product for generating a multi-document summary is provided. The embodiment may include receiving a query statement, one or more documents, one or more summary constraints, and quality goals. The embodiment may include identifying one or more keywords within the query statement. The embodiment may include performing a sentence selection from the one or more documents based on the one or more identified keywords. The embodiment may include generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the goals, and a cross entropy method. The embodiment may include calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features. The embodiment may include selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold.

Abstract: Automated keyphrase extraction from a digital text document. A pool of candidate keyphrases of the digital text document is created. A cross-entropy method is then employed to compute a set of output keyphrases out of the pool of candidate keyphrases, by iteratively optimizing an objective function that is configured to cause the set of output keyphrases to be descriptive of one or more main topics discussed in the digital text document. The set of output keyphrases may be used for at least one of: text summarization, text categorization, opinion mining, and document indexing.

Abstract: A method comprising receiving digital documents, a query statement, and a summary length constraint; identifying, for each of said digital documents, a sentence subset, based, at least in part, on said query statement, a modified version of said summary length constraint, and a first set of quality objectives, generating, for each of said sentence subsets, a random forest representation; iteratively (i) sampling, from each of said random forest representations, a plurality of tokens to create a corresponding candidate document summary, based, at least in part, on weights assigned to each of said tokens, (ii) assigning a quality ranking to said candidate document summary, based, at least in part, on said first set of quality objectives and a second set of quality objectives, and (iii) adjusting said weights, based, at least in part, on said quality rankings; and outputting a highest ranking said candidate document as a compressed summary.

Abstract: Embodiments may provide automated summarization of documents, such as scientific documents by using a prior distribution on logical sections learnt from a corpus of human authored summaries. For example, a method of document summarization may comprise receiving, at the computer system, a document and segmenting the document into a plurality of sentences, identifying, at the computer system, sections in the document and aligning each sentence in the document to a section logical role, and summarizing, at the computer system, the document using a probability distribution.

Abstract: Embodiments may provide automated summarization of documents, such as scientific documents by using a prior distribution on logical sections learnt from a corpus of human authored summaries. For example, a method of document summarization may comprise receiving, at the computer system, a document and segmenting the document into a plurality of sentences, identifying, at the computer system, sections in the document and aligning each sentence in the document to a section logical role, and summarizing, at the computer system, the document using a probability distribution.

Abstract: A system for generating a multi-modal summary of a digital document, comprising a processor adapted for: extracting from the document a plurality of graphical elements; generating a set of textual descriptions, each generated for one of the graphical elements and associated therewith; selecting, from the set of textual descriptions and a set of text fragments extracted from the document, a set of representative elements having a highest score computed by applying thereto a score function, where a set of representative elements' score is indicative of a degree by which the set of representative elements represents the document; for each representative element of the set of representative elements, where the element is a textual description of a graphical element of the plurality of graphical elements, replacing the element with the graphical element associated therewith; and generating, using the set of representative elements, another document comprising a multi-modal summary of the document.

Abstract: Automated keyphrase extraction from a digital text document. A pool of candidate keyphrases of the digital text document is created. A cross-entropy method is then employed to compute a set of output keyphrases out of the pool of candidate keyphrases, by iteratively optimizing an objective function that is configured to cause the set of output keyphrases to be descriptive of one or more main topics discussed in the digital text document. The set of output keyphrases may be used for at least one of: text summarization, text categorization, opinion mining, and document indexing.

Abstract: A method comprising receiving digital documents, a query statement, and a summary length constraint; identifying, for each of said digital documents, a sentence subset, based, at least in part, on said query statement, a modified version of said summary length constraint, and a first set of quality objectives, generating, for each of said sentence subsets, a random forest representation; iteratively (i) sampling, from each of said random forest representations, a plurality of tokens to create a corresponding candidate document summary, based, at least in part, on weights assigned to each of said tokens, (ii) assigning a quality ranking to said candidate document summary, based, at least in part, on said first set of quality objectives and a second set of quality objectives, and (iii) adjusting said weights, based, at least in part, on said quality rankings; and outputting a highest ranking said candidate document as a compressed summary.

Abstract: A computerized method comprising using hardware processors for receiving a constraint satisfaction problem (CSP) from a constraint solver system that previously reached a timeout error. The CSP comprises two or more constraints. The hardware processor(s) are used for determining one or more timeout cores of constraints by iteratively removing some test constraints from the CSP thereby forming a sub-problem, and solving the sub-problem using the constraint solver system. When the constraint solver system determines that the sub-problem is solvable the test constraints are added to the timeout cores and the test constraint returning to the CSP, otherwise the sub-problem is assigned as the CSP for the subsequent iteration. The timeout cores are sent to a user terminal for presentation to a user, and receiving a user input to resolve the timeout error of the CSP.

Abstract: A method, computer system, and computer program product for generating a multi-document summary is provided. The embodiment may include receiving a query statement, one or more documents, one or more summary constraints, and quality goals. The embodiment may include identifying one or more keywords within the query statement. The embodiment may include performing a sentence selection from the one or more documents based on the one or more identified keywords. The embodiment may include generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the goals, and a cross entropy method. The embodiment may include calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features. The embodiment may include selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold.

Abstract: A method, computer system, and computer program product for generating a multi-document summary is provided. The embodiment may include receiving a query statement, one or more documents, one or more summary constraints, and quality goals. The embodiment may include identifying one or more keywords within the query statement. The embodiment may include performing a sentence selection from the one or more documents based on the one or more identified keywords. The embodiment may include generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the goals, and a cross entropy method. The embodiment may include calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features. The embodiment may include selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold.

Abstract: A method, computer system, and computer program product for generating a multi-document summary is provided. The embodiment may include receiving a query statement, one or more documents, one or more summary constraints, and quality goals. The embodiment may include identifying one or more keywords within the query statement. The embodiment may include performing a sentence selection from the one or more documents based on the one or more identified keywords. The embodiment may include generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the goals, and a cross entropy method. The embodiment may include calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features. The embodiment may include selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold.

Abstract: A method and product for solving a Constraint Satisfaction Problem (CSP) having a constraint associated with a string variable, comprising: defining a string variable using a string domain data structure representing a domain of string values for string variables, the structure represents the domain as a Deterministic Finite Automaton (DFA) with no back loops longer than 1 and edges representing characters; defining a constraint for the CSP, wherein the constraint involves the variable and is to be complied with by a solution to the CSP; invoking a CSP solver using the string variable while complying with the constraint, and to invoke operations performed over the domain, wherein the solver: propagates values into the domain of string values, wherein the value propagation reduces the domain size; or selects values from the domain thus reducing the domain to a singleton domain, whereby value propagation to domains of other variables is invoked by the solver.

Abstract: A method, computer system, and computer program product for generating a multi-document summary is provided. The embodiment may include receiving a query statement, one or more documents, one or more summary constraints, and quality goals. The embodiment may include identifying one or more keywords within the query statement. The embodiment may include performing a sentence selection from the one or more documents based on the one or more identified keywords. The embodiment may include generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the goals, and a cross entropy method. The embodiment may include calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features. The embodiment may include selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold.

Abstract: A method and product for solving a Constraint Satisfaction Problem (CSP) having a constraint associated with a string variable, comprising: defining a string variable using a string domain data structure representing a domain of string values for string variables, the structure represents the domain as a Deterministic Finite Automaton (DFA) with no back loops longer than 1 and edges representing characters; defining a constraint for the CSP, wherein the constraint involves the variable and is to be complied with by a solution to the CSP; invoking a CSP solver using the string variable while complying with the constraint, and to invoke operations performed over the domain, wherein the solver: propagates values into the domain of string values, wherein the value propagation reduces the domain size; or selects values from the domain thus reducing the domain to a singleton domain, whereby value propagation to domains of other variables is invoked by the solver.

Abstract: A computerized method comprising using hardware processors for receiving a constraint satisfaction problem (CSP) from a constraint solver system that previously reached a timeout error. The CSP comprises two or more constraints. The hardware processor(s) are used for determining one or more timeout cores of constraints by iteratively removing some test constraints from the CSP thereby forming a sub-problem, and solving the sub-problem using the constraint solver system. When the constraint solver system determines that the sub-problem is solvable the test constraints are added to the timeout cores and the test constraint returning to the CSP, otherwise the sub-problem is assigned as the CSP for the subsequent iteration. The timeout cores are sent to a user terminal for presentation to a user, and receiving a user input to resolve the timeout error of the CSP.