International Business Machines Corporation

Kiran Mehta

Hui-I Hsiao

Scott Holmes

Sachindra Joshi

Inderpal Singh Narang

Raghuram Krishnapuram

Sumit Negi

Ajay Kumar Sood

Ana Lelescu

Neeraj Agrawal

Hongcheng Mi

Ganesh Ramakrishnan

Nimit Kumar

A method () is disclosed of extracting factoids from text repositories, with the factoids being associated with a given factoid category. The method () starts by training a classifier () to recognize factoids relevant to that given factoid category. Documents or document summaries relevant to the given factoid category is next collected () from the text repositories. Sentences having a predetermined association to the given factoid category is extracted () from the documents or said document summaries. Those sentences are classified (), in a noisy environment, using the classifier () to extract snippets containing phrases relevant to the given factoid category. It is the extracted snippets that are the factoid associated with the given factoid category.

System and method for extraction of factoids from textual repositories

A cost efficient solution for supporting and deploying custom text analytics applications suited is to provide third party application developers a sand-boxed application development environment such as an appliance computer system, allowing users to leverage data integration, indexing and pre-existing mining platform capabilities for a domain-specific data. Thus, embodiments herein present a system, method, etc. for identifying and delivering domain specific unstructured content for advanced business analysis. The system generally comprises a cluster computer system, a gateway computer system and an appliance computer system.

Automated process for identifying and delivering domain specific unstructured content for advanced business analysis

A database management system and associated methods for parallelizing file archival and retrieval in an extended database management system. The system includes a set of copy agents that selectively acquire the backup tasks from a copy queue, and a set of retrieval agents that selectively acquire the restore tasks from a restore queue. The chances of contention between any two copy agents or any two retrieve agents acquiring the same copy or restore task is significantly minimized. Once specific copy agents are assigned backup tasks, the backup process is implemented to determine the optimal way to write the backup files to one or more targets, in parallel. In addition, the present system enables the efficient and expeditious retrieval of the desired files without having to search all the targets.

System and method for parallelizing file archival and retrieval

Recovery of a filesystem directory structure is performed to restore it to any point in time and also to synchronize a database restore and a filesystem restore to bring the two restores to a database consistent state. A database management system (DBMS) manages external files and hierarchical directory structures to enable recovery and reconciliation of the files and filesystems, under DBMS control, after filesystem crashes. First, a database table, which recorded previous directory creations and deletions, is used to rebuild a filesystem's directory structure to any previous database state and then external file link information is used to restore files to that same state.

Method for database assisted file system restore

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Castro Valley, CA, United States of America

Kiran Mehta