International Business Machines Corporation

Iqlect Software Solutions Pvt Ltd.

Prasad Manikarao Deshpande

Deepak S Padmanabhan

Mukesh Kumar Mohania

Karin Murthy

Raghuram Krishnapuram

Rajeev Gupta

Salil Joshi

Scott Schumacher

Vijil Enara Chenthamarakshan

Atreyee Dey

Sriram Kolinjivadi Padmanabhan

Rema Ananthanarayanan

Debapriyo Majumdar

Shajeer K Mohammed

Vinatha Chaturvedi

Jennifer S Reed

Krishna Kummamuru

Sanjeev K Gupta

Sriram Raghavan

Savitha Srinivasan

Vishal Singh Batra

Girish Venkatachaliah

Sheshnarayan Agrawal

Animesh Nandi

Suriya Subramanian

Ramanujam Seshadri Halasipuram

Balakrishna Raghavendra Iyer

Biplav Srivastava

Arnon Amir

Vijay Krishnarao Naik

Manoj Kumar Agarwal

Akshar Kaul

Sachin Gupta

Manish Kesarwani

Sumit Negi

Dinesh Garg

Guruduth Somasekhara Banavar

Gagandeep Singh

Sriram Padmanabhan

Songhua Xing

Vladimir Zbarsky

Ullas Balan Nambiar

Narendran Sachindran

Ashu Gupta

Raghavendra Uppinakuduru Udupa

Mahesh Dhabade

Sachin Sinha

Aditya Telang

Jayant R Haritsa

Bruhathi H Sundarmurthy

Sayan Ranu

Ramakrishna Varadarajan

Vijii Enara Chenthamarakshan

Mangesh Kute

The present disclosure provides a method and system for a scalable complex event processing of event streams. The method includes reception of one or more input event streams and collection of one or more output event streams. Further, the method includes modeling of each instance of each input event stream and each instance of the plurality of instances for intermediate states as records of a database table. The method includes indexing of each record of the database table and distribution of a first set of records in temporary memory and the second set of records in one or more persistent storage devices. The method includes flushing the second set of records of the database table in one or more persistent storage devices and querying of the plurality of records of the database table. The method includes inferring one or more complex events from transition of a plurality of states.

Method and system for scalable complex event processing of event streams

Methods, systems, and computer program products for categorizing log records at run-time are provided herein. A computer-implemented method includes generating one or more template signatures to be associated with each of multiple templates, wherein each of the multiple templates comprises a concatenation of one or more words; processing each of multiple log records derived from a data stream to determine a composition of each of the multiple log records; matching one or more of the generated template signatures to each of the multiple log records based on the determined composition of each of the multiple log records; and outputting an identification of (i) each of the multiple log records and (ii) the one or more generated template signatures matched thereto.

Categorizing log records at run-time

A call center system for allocating problem tickets for technical services by using a pull model auction to select an agent to work on the problem ticket. When the call center receives an order for a technical service, it develops a complexity estimate for the tasks specified in the problem ticket, and calculates deadlines for completing the problem ticket and for conducting the auction. Invitations to bid on the problem ticket are sent to potential agents on a bidder's list. The winning bid is selected from among the bids received back from the potential agents, and, after evaluating the bids, the problem ticket is transferred to the winning agent.

Reverse auction based pull model framework for workload allocation problems in IT service delivery industry

Methods, systems, and computer program products for organizing on-disk layout of index structures are provided herein. A method includes organizing an on-disk corpus of data index structures; partitioning each data index structure into an active and/or latest state data partition and an archived data partition; sub-partitioning each of the archived data partitions into sub-partitions based on exact lifespan of each data item; executing a search query that includes temporal predicates and keyword predicates across the corpus by: pruning a collection of identified items of data from the corpus that contain the keyword predicates using range metadata associated with the temporal predicates to generate a pruned list of data items; and performing a list intersection operation on the data index structures to generate a list of common data items from the pruned list; retrieving the common data items from the active and/or latest state data partitions and the archived data sub-partitions.

Organizing on-disk layout of index structures to support historical keyword search queries over temporally evolving data

Entity mappings that produce matching entities for a first data asset having attributes and a second data asset having attributes are generated by: generating entity mappings that produce matching entities for a first data asset having attributes with attribute values and a second data asset having attributes with attribute values by: matching the attribute values of the attributes of the first data asset with the attribute values of the attributes of the second data asset, using the matching attribute values to generate matching attribute pairs, and using the matching attribute pairs to identify entity mappings; computing an entity mapping score for each of the entity mappings based on a combination of factors; ranking the entity mappings based on each entity mapping score; and using some of the ranked entity mappings to determine whether a same real-world entity is described by the first data asset and the second data asset.

Identifying entity mappings across data assets

Methods, systems, and computer program products for securely processing range predicates on cloud databases are provided herein. A computer-implemented method includes separately encrypting a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items; converting a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combining results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query.

Securely processing range predicates on cloud databases

Methods and arrangements for discovering entity types for a set of records. A set of records is input, with each record comprising attributes with associated attribute values. The records are grouped into candidate entity types in view of at least one of: the attribute values of the records, at least one domain ontology and at least one dimension hierarchy. An interestingness measure of each candidate entity type is calculated, via estimating interestingness based on at least one factor selected from the group consisting of: a correlation between attribute values of records, a number of attributes, a log of queries issued to a server, and an average group size for candidate entity types. At least one candidate entity type is validated based on the calculated interestingness measures. Other variants and embodiments are broadly contemplated herein.

Discovery of related entities in a master data management system

Techniques, systems, and articles of manufacture for collaborative analytics with edge devices. A method includes identifying multiple items of data pertaining to a user from one or more user actions implemented across multiple user devices, identifying one or more rules associated with one or more user preferences, exchanging the multiple items of data across the multiple user devices, and applying the one or more rules to the multiple items of data across the multiple user devices to generate an output via at least one of the multiple user devices.

Collaborative analytics with edge devices

Embodiments of the present invention disclose a method, computer program product, and system for identifying matching products relative to a reference product. A reference product is identified from a received product query and a query is generated based on the reference product. A generated query comprises of an ontology, at least one word appearing in a title of the reference product, and a set of key words appearing in social media data associated with the reference product. A database is searched using the generated query to find matching product sets and the results are returned and filtered. Results are filtered by calculating a relationship score between the reference product and one or more matching products in the set of matching products, and/or by filtering a subset of the set of matching products based on a customer profile. The filtered subset of results are communicated to a recipient.

Product recommendations over multiple stores

A method for supplementing structured information within a data system for entities based on unstructured data analyzes a document with unstructured data and extracts attribute values from the unstructured data for one or more entities of the data system. Entity records with structured information are retrieved from the data system based on the extracted attribute values. Entity references for corresponding entities of the data system are constructed based on a comparison of the retrieved entity records and the extracted attribute values. The entity references are linked to the corresponding entities within the data system, with the entity references including extracted attributes from the unstructured data for corresponding linked entities.

Supplementing structured information about entities with information from unstructured data sources

Methods and arrangements for identifying root causes of system failures in a distributed system said method including: utilizing at least one processor to execute computer code that performs the steps of: recording, in a storage device, collected machine state data, wherein the collected machine state data are added to historical machine state data; creating, based on the historical machine state data, a healthy map model; detecting at least one failed machine state in the distributed system; comparing the failed machine state against the healthy map model; identifying, based on the comparison, at least one root cause of the failed machine state; and displaying, on a display device, a ranked list comprising the at least one root cause. Other variants and embodiments are broadly contemplated herein.

Identifying root causes of failures in a deployed distributed application using historical fine grained machine state data

Methods, systems, and computer program products for distributed iceberg cubing over ordered dimensions are provided herein. A method includes calculating, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions; pruning the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures; and determining a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions.

Distributed iceberg cubing over ordered dimensions

Methods and arrangements for measuring similarity with respect to moving object trajectories. First and second moving object trajectories are input, each trajectory being defined by at least two spatial dimensions and a temporal dimension. At least one segment is defined with respect to each trajectory, each segment being defined between two defining points. At least one segment from the first trajectory is matched with at least one segment from the second trajectory. A spatial distance and temporal distance are each computed between the at least one segment from the first trajectory and the at least one segment from the second trajectory. The spatial distance and temporal distance are combined to provide a measure of a spatio-temporal distance between the at least one segment from the first trajectory and the at least one segment from the second trajectory. Other variants and embodiments are broadly contemplated herein.

Computing a similarity measure over moving object trajectories

Methods and arrangements for identifying related data in different data sets to assist in searching the data sets. A first data asset and a second data asset are accessed. Common entities are identified between the first and second data assets. A score is determined for the relationship between the first and second data assets, based on the identified common entities. One or more relationship contexts are determined for the relationship between the first and second data assets, and the relationship score and one or more relationship contexts are used to join at least a portion of each of the first and second data assets as a basis for subsequent searching. Other variants and embodiments are broadly contemplated herein.

Contextualization of entity relationships

Growing community of inventors

Mumbai, India

Prasad Manikarao Deshpande