Accenture Global Services Gmbh

Peter Z Yeh

Kunal Verma

Doo Soon Kim

Harsha Kumar Srivatsa

Alex M Kass

Karthik Rajagopal Gomadam

Lucian P Hughes

Reymonrod Geli Vasquez

Colin Anil Puri

Prateek Jain

Mark Gilbert Kobe

A technology analysis system automatically monitors information available from both publicly and privately distributed networks of information for details that are relevant to a technology hypothesis. The technology analysis system provides a technology radar that assists with determining how the technology hypothesis stands up against ongoing developments in technology. The technology analysis system also visualizes the technology hypothesis and its underlying precursor predictions using a web portal, dynamic document, or other visualization technique.

Technology event detection, analysis, and reporting system

A data lineage tracking system may include a memory storing a module comprising machine readable instructions to obtain trace log entries representing an interaction with, a manipulation of, and/or a creation of a data value. The data lineage tracking system may further include machine readable instructions to select the trace log entries that are associated with commands performed by an application, cluster similar trace log entries from the selected trace log entries, and analyze mappings between the clustered trace log entries to determine data lineage flow associated with the data value.

Data lineage tracking

A corpus of textual listings is received and main concept words and attribute words therein are identified via an iterative process of parsing listings and expanding a semantic model. During the parsing phase, the corpus of textual listings is parsed to tag one or more head noun words and/or one or more identifier words in each listing based on previously identified main concept words or using a head noun identification rule. Once substantially each listing in the corpus has been parsed in this manner, the expansion phase assigns head noun words as main concept words and modifier words as attribute words, where possible. During the next iteration, the newly identified main concept words and/or attribute words are used to further parse the listings. These iterations are repeated until a termination condition is reached. Remaining words in the corpus are clustered based on the main concept words and attribute words.

Generation of a semantic model from textual listings

A data enrichment system may include an attribute relevance module to measure relevance of an attribute to a data object to be enriched. The data object may include the attribute including a known or an unknown value. An output value confidence module may calculate a confidence of an output value of a source used for enrichment of the data object. The output value may represent the known and/or unknown values of the attribute. The system may use the measured relevance of the attribute and the calculated confidence of the output value to determine assignment of the known or unknown values to the attribute.

Data enrichment using heterogeneous sources

A data mapping acceleration system may include a syntactic profile module to generate a syntactic profile of a data source to be mapped. A semantic classification module may generate a semantic classification of the data source. A similarity module may evaluate the syntactic profile and semantic classification to determine an overall similarity between attributes of data from the data source for mapping the data source.

Data mapping acceleration

An information source alignment system may include a tree generation module executed by a computer system to generate a source category hierarchy tree for a source class in a first information source and a target category hierarchy tree for a target class in a second information source. The source and target category hierarchy trees may be constructed from a class hierarchy of a knowledge source. A class-similarity determination module may compare the source and target category hierarchy trees. An alignment module may determine whether the source and target classes are aligned based on the comparison of the source and target category hierarchy trees.

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San Jose, CA, United States of America

Peter Z Yeh