International Business Machines Corporation

Min Wang

Lipyeow Lim

Haixun Wang

George Andrei Mihaila

John Sidney Davis, Ii

Sriram Kolinjivadi Padmanabhan

Yuan-Chi Chang

Anastasios Kementsietsidis

Maria Rene Ebling

Balakrishna Raghavendra Iyer

Daby Mousse Sow

Archan Misra

Marion Lee Blount

Chitra Venkatramani

Zhen Zhang

Charu Chandra Aggarwal

Achille Belly Fokoue-Nkoutche

Aditya Anand Kalyanpur

Kavitha Srinivas

Thomas Abel Beavin

Christian Alexander Lang

Akira Shibamiya

Hong Sang Tie

Chung-Sheng Li

John Richard Smith

Kun-Lung Wu

Philip Shilung Yu

Milind R Naphade

Brian Patrick Byrne

Oktie Hassanzadeh

Lisa Amini

Wim De Pauw

Matthew Leon Hill

Ramesh Chandra Agarwal

Songyun Duan

Xiaohui Gu

Murray Scott Campbell

Kirill M Osipov

Wangchao Le

Peixiang Zhao

Jingmin He

A computer-implemented method, system, and computer program product for producing a semantic query by example are provided. The method includes receiving examples of potential results from querying a database table with an associated ontology, and extracting features from the database table and the examples based on the associated ontology. The method further includes training a classifier based on the examples and the extracted features, and applying the classifier to the database table to obtain a semantic query result. The method also includes outputting the semantic query result to a user interface, and requesting user feedback of satisfaction with the semantic query result. The method additionally includes updating the classifier and the semantic query result iteratively in response to the user feedback.

Semantic query by example

A computer-implemented method, system, and program product for automatically reviewing a mapping between information models. The method includes: receiving a mapping between an element in the first information model to an element in the second information model. Each element is associated with an element identifier and an element value, and the mapping signifies a relationship between the element in the first information model and the element in the second information model. The method further includes comparing the received mapping against one or more known indications of suspicious mappings to determine if the received mapping resembles one of the indications of suspicious mappings. If the received mapping is determined to be suspicious, identifying the received mapping as one that requires review.

Automatically reviewing information mappings across different information models

A system and method for managing provenance data are disclosed. In accordance with one method, input data elements assessed by a processing element are evaluated. The method further includes determining whether an input window comprising the input data elements includes a sufficient amount of relevant input data. If the input window does not include a sufficient amount of relevant input data, then the input data elements are designated for reference in response to a provenance query.

System and method for provenance function window optimization

A method, system, and computer readable medium for collecting statistics associated with data in a database are disclosed. The computer readable medium implements the method comprises determining an amount of memory needed to collect statistics for data associated with a defined data type in a relational database. The defined data type is based upon a mark-up language using a tree structure with one or more root-to-node paths therein. The amount of memory is allocated as determined for collecting the statistics for the data of the defined data type. A statistics collection is performed for the data of the defined data type in a single pass through the database and within the amount of memory which has been allocated. The performing includes at least determining a total number of instances of at least one path-identifier associated with a given value within a given set of documents.

Statistics collection using path-value pairs for relational databases

Techniques for indexing provenance data and evaluating provenance data queries are disclosed. For example, a method for processing one or more queries directed toward data associated with a data processing system comprises the following steps. One or more data items of a first data set associated with the data processing system are mapped to a first representation type and one or more data items of a second data set associated with the data processing system are mapped to a second representation type. A bi-directional index of a data provenance relation existing between the data items of the first data set and the data items of the second data set is computed. The bi-directional index is computed in terms of the first representation type and the second representation type. A query evaluation is performed using the bi-directional index, in response to receipt of a provenance query. The bi-directional index is used for query evaluation whether the received provenance query is a backward provenance query or a forward provenance query. A response is generated for the received provenance query based on a result of the query evaluation. In one further example, the provenance query evaluation step may be performed by using only the bi-directional index and does not require access to base data or maintaining stored provenance data.

Indexing provenance data and evaluating provenance data queries in data processing systems

Interoperability is enabled between participants in a network by determining values associated with a value metric defined for at least a portion of the network. Information flow is directed between two or more of the participants based at least in part on semantic models corresponding to the participants and on the values associated with the value metric. The semantic models may define interactions between the participants and define at least a portion of information produced or consumed by the participants. The determination of the values and the direction of the information flow may be performed multiple times in order to modify the one or more value metrics. The direction of information flow may allow participants to be deleted from the network, may allow participants to be added to the network, or may allow behavior of the participants to be modified.

Enabling interoperability between participants in a network

A method of performing a graph query issued by a user is provided. The method includes performing on a processor, receiving a user graph query. The method includes rewriting the user graph query as a new query based on a query policy expressed in a graph query language. The method includes performing the new query on graph data to obtain a result.

Enforcing query policies over resource description framework data

Techniques are disclosed for determining and validating provenance data in such data stream processing systems. For example, a method for processing data associated with a data stream received by a data stream processing system, wherein the system comprises a plurality of processing elements, comprises the following steps. Input data elements and output data elements associated with at least one processing element of the plurality of processing elements are obtained. One or more intervals are computed for the processing element using data representing observations of associations between inputs elements and output elements of the processing element, wherein, for a given one of the intervals, one or more particular input elements contained within the given interval are determined to have contributed to a particular output element. In another method, intervals are specified, and then validated by comparing the specified intervals against intervals computed based on observations.

Determining and validating provenance data in data stream processing system

Disclosed are a method, information processing system, and computer readable medium for processing queries. The method includes receiving a data query for a set of hierarchical markup documents. At least one query path expression is extracted from the data query. The query path is processed against at least one shared hierarchical markup document in a plurality of shared hierarchical markup documents. The plurality of shared hierarchical documents is associated with the set of hierarchical markup documents. In response to the shared hierarchical markup document completely matching the query path expression, a query result for the data query is generated. The query result is based on the processing of the query path expression against at least one of the shared hierarchical markup document and the difference hierarchical markup document.

Processing queries on hierarchical markup data using shared hierarchical markup trees

Techniques for estimating items (e.g., data item or objects) frequencies in large data sets are disclosed. For example, a technique for determining items and their frequencies at multiple levels of interest in a collection of nested bags includes the following steps. A hierarchy of a plurality of levels of nested bags and the levels of interest are inputted. Among the plurality of levels, a subset of bags is sampled from at least one level. At each level of interest, the frequency is counted of each distinct item in the bags obtained in the sampling step. At each level of interest, the item frequencies obtained in the counting step are extrapolated based on sampling ratios associated with the sampling step. At each level of interest, the items are sorted according to their frequencies obtained from the extrapolating step and those items with highest frequencies are retained. A bag may refer to one or more subsets or groups of data items or objects. Also, a bag may, itself, contain one or more other bags.

Techniques for estimating item frequencies in large data sets

A method of semantic-aware record matching includes receiving source and target string record specifications associated with a source string record and a target string record, receiving semantic knowledge referring to tokens of the source string record and target string record, creating a first set of tokens for the source string record and a second set of tokens for the target string record based on the semantic knowledge, assigning a similarity score to the source string record and the target string record based on a semantic relationship between the first set of tokens and the second set of tokens, and matching the source string record and the target string record based on the similarity score.

Semantic-aware record matching

A method for executing a query on a graph data stream. The graph stream comprises data representing edges that connect vertices of a graph. The method comprises constructing a plurality of synopsis data structures based on at least a subset of the graph data stream. Each vertex connected to an edge represented within the subset of the graph data stream is assigned to a synopsis data structure such that each synopsis data structure represents a corresponding section of the graph. The method further comprises mapping each received edge represented within the graph data stream onto the synopsis data structure which corresponds to the section of the graph which includes that edge, and using the plurality of synopsis data structures to execute the query on the graph data stream.

Query optimization over graph data streams

A system and method for selection of a provenance dependency function in a stream-based data processing infrastructure to optimize backtracing performance in response to a provenance query includes determining performance of a set of dependency functions associated with an analysis component for determining relevancy of each input event received by the analysis component. The relevancy of each input event is determined according to each dependency function and storing a record of relevant events according to a recording method. Relevancy results of the dependency functions are aggregated, and the dependency functions are ordered according to a criterion. Data provenance is provided for a given output event using the input event recording method associated with a best dependency function according to the criterion.

Methods, apparatus and systems, including computer program products, for reducing an error rate when mapping entities between a first ontology and a second ontology. One or more of a general language dictionary and an industry-specific dictionary are provided. Natural language processing of the first ontology is performed to identify one or more candidate relationship entities in the first ontology. Each candidate relationship entity includes a compound name having two or more semantic labels, and each candidate relationship entity has a name that neither exists in the general language dictionary or the industry-specific dictionary. Each of the one or more candidate relationship entities in the first ontology is mapped to one or more entities in the second ontology using one or more configurable computer-implemented mapping algorithms.

Mapping of relationship entities between ontologies

Techniques are disclosed for maintaining and processing provenance data in such data stream processing systems. For example, a method for processing data associated with a data stream received by a data stream processing system, wherein the system comprises a plurality of processing elements, comprising the following steps. A portion of data associated with the data stream is maintained. The maintained data comprises inputs to each processing element that contributed to an output of each processing element. In response to an alert generated by one of the processing elements, a scheduler is triggered to determine when a pre-calculation of a prospective query related to the alert should be executed. In response to the scheduler, at least a portion of the maintained data is used to determine a set of data that contributed to the alert such that the alert-contributing set of data can be used to respond to the prospective query upon arrival thereof.

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Cortlandt Manor, NY, United States of America

Min Wang