Abstract: Systems and methods include intercepting traffic on the user device; forwarding the traffic to a cloud-based system for security processing therein; and, responsive to unavailability of the cloud-based system preventing the forwarding, performing local security processing of the traffic at the user device including determining whether the traffic is allowed based on a cache at the user device, forwarding the traffic separate from the cloud-based system when it is allowed, and blocking the traffic when it is not allowed.

Abstract: Described herein is a method of context aware chat categorization for business decisions. A business category of the chat presented by the viewer/user on a platform is predicted and groups of chats having similar context and created and arranged in an ordered score indicative of importance. The categorization method includes applying LSTM's in parallel with shared embeddings on said user data, applying an LSTM technique to determine sentence similarity, applying the user's social connectivity in the form of Eigen-centrality of its connectivity on said platform, determining the customised loss function, grouping of chats in categories based on context, context based grouping of chats wherein context is obtained from chat description, and determining attention score based on textual representation of human emotions such as emojis, repetitive characters, and words for each group of chats in a category.

Abstract: A system and method for continuous processing of data streams residing in distributed data sources. The method includes: receiving a plurality of data streams from a plurality of distributed data sources; processing each of the plurality of data streams using a plurality commands, the plurality commands are executed in parallel using a graph execution engine; and transporting, through a transport layer, each of the plurality of data streams using the plurality commands to at least one data sink.

Abstract: A system and method for performing a hash bucketing process on data in motion are presented. The method includes applying a first hash function on an input dataset to map the input dataset to a bucket, wherein the first hash function results with a first hash value; applying a second hash function on the first hash value to map the input dataset to a record in the bucket; generating metadata based on the input dataset, wherein the metadata at least points to the original location of the input dataset; and storing the generated metadata in the record in the bucket.

Abstract: A system and method for data entries deduplication are provided. The method includes indexing an input data set, wherein the input data set is in a tabular formant and the indexing includes providing a unique Row identifier (RowID), wherein rows are the data entries; computing attribute similarity for each column across each pair of rows; computing, for each pair of rows, row-to-row similarity as a weighted sum of attribute similarities; clustering pairs of rows based on their row-to-row similarities; and providing an output data set including at least the clustered pairs of rows.

Abstract: A system and computer implemented method for cataloging database metadata using a signature matching process are provided. The method includes receiving an input name to be matched to a key in a seed table; generating a first fingerprint by decomposing the received input name into a first set n-grams; generating, based on the received input name, a second fingerprint using a predetermined pronunciation schema, wherein the second fingerprint is a phonetic fingerprint; generating a third fingerprint by decomposing the second fingerprint into a second set of n-grams; identifying a matching key by matching any combination of the first fingerprint, the second fingerprint, and the third fingerprint against keys in the seed table; and cataloging the metadata with the matching key as a tag.

Abstract: A method and system for tagging database columns are presented. The method includes receiving an input column name of at least one column in a database; performing signature matching of the input column name to contents of a seed table; determining a first confidence score for the signature matching; and tagging a matching value in the seed table as a tag for the input column name, when a first confidence score exceeds a first threshold value.

Abstract: A system and computer implemented method for cataloging database metadata using a probabilistic signature matching process are provided. The method includes receiving an input name to be matched to keys in a data corpus; dividing the received input name into a plurality of text segments; identifying a set of matching keys by matching each of the plurality text segments against keys in the data corpus; analyzing the set of matching keys to construct a tag; and cataloging the metadata with the matching key as the construct tag.

Abstract: A method and an inclusion dependency determination system (IDDS) for determining inclusion dependency between columns of tables in a target database to establish primary key (PK)-foreign key (FK) relationships among data in the columns with minimized disk input and output operations are provided. The IDDS determines dependency characteristic data (DCD) of each column and arranges the columns by applying one or more predefined rules to the columns based on a minimum value of the data of each column. The IDDS determines pairs of arranged columns that demonstrate a possibility of inclusion dependency based on the DCD and identifies a first column and a second column of each determined pair as a candidate PK and a candidate FK respectively. The IDDS determines inclusion dependency between the candidate PK and the candidate FK on comparing data of the candidate PK with the data of the candidate FK using dynamically determined search techniques.

Abstract: A system and method for data entries deduplication are provided. The method includes indexing an input data set, wherein the input data set is in a tabular formant and the indexing includes providing a unique Row identifier (RowID), wherein rows are the data entries; computing attribute similarity for each column across each pair of rows; computing, for each pair of rows, row-to-row similarity as a weighted sum of attribute similarities; clustering pairs of rows based on their row-to-row similarities; and providing an output data set including at least the clustered pairs of rows.

Abstract: A system and method for performing a hash bucketing process on data in motion are presented. The method includes applying a first hash function on an input dataset to map the input dataset to a bucket, wherein the first hash function results with a first hash value; applying a second hash function on the first hash value to map the input dataset to a record in the bucket; generating metadata based on the input dataset, wherein the metadata at least points to the original location of the input dataset; and storing the generated metadata in the record in the bucket.

Abstract: A system and method for continuous processing of data streams residing in distributed data sources. The method includes: receiving a plurality of data streams from a plurality of distributed data sources; processing each of the plurality of data streams using a plurality commands, the plurality commands are executed in parallel using a graph execution engine; and transporting, through a transport layer, each of the plurality of data streams using the plurality commands to at least one data sink.

Abstract: A system and computer implemented method for cataloging database metadata using a probabilistic signature matching process are provided. The method includes receiving an input name to be matched to keys in a data corpus; dividing the received input name into a plurality of text segments; identifying a set of matching keys by matching each of the plurality text segments against keys in the data corpus; analyzing the set of matching keys to construct a tag; and cataloging the metadata with the matching key as the construct tag.

Abstract: A system and computer implemented method for cataloging database metadata using a signature matching process are provided. The method includes receiving an input name to be matched to a key in a seed table; generating a first fingerprint by decomposing the received input name into a first set n-grams; generating, based on the received input name, a second fingerprint using a predetermined pronunciation schema, wherein the second fingerprint is a phonetic fingerprint; generating a third fingerprint by decomposing the second fingerprint into a second set of n-grams; identifying a matching key by matching any combination of the first fingerprint, the second fingerprint, and the third fingerprint against keys in the seed table; and cataloging the metadata with the matching key as a tag.

Abstract: A method and system for tagging database columns are presented. The method includes receiving an input column name of at least one column in a database; performing signature matching of the input column name to contents of a seed table; determining a first confidence score for the signature matching; and tagging a matching value in the seed table as a tag for the input column name, when a first confidence score exceeds a first threshold value.

Abstract: A method and an inclusion dependency determination system (IDDS) for determining inclusion dependency between columns of tables in a target database to establish primary key (PK)-foreign key (FK) relationships among data in the columns with minimized disk input and output operations are provided. The IDDS determines dependency characteristic data (DCD) of each column and arranges the columns by applying one or more predefined rules to the columns based on a minimum value of the data of each column. The IDDS determines pairs of arranged columns that demonstrate a possibility of inclusion dependency based on the DCD and identifies a first column and a second column of each determined pair as a candidate PK and a candidate FK respectively. The IDDS determines inclusion dependency between the candidate PK and the candidate FK on comparing data of the candidate PK with the data of the candidate FK using dynamically determined search techniques.

Abstract: In one embodiment, one or more search criteria are received from a mobile device. In response, one or more products corresponding to the search criteria are extracted. Further, a plurality of factors associated with the one or more products are retrieved and weightages are assigned to the plurality of factors. Furthermore, product scores of the one or more products are determined based on the plurality of factors and the weightages. Based on the product scores, the one or more products are presented to assist product searching in retail environment.

Abstract: In one embodiment, one or more search criteria are received from a mobile device. In response, one or more products corresponding to the search criteria are extracted. Further, a plurality of factors associated with the one or more products are retrieved and weightages are assigned to the plurality of factors. Furthermore, product scores of the one or more products are determined based on the plurality of factors and the weightages. Based on the product scores, the one or more products are presented to assist product searching in retail environment.