International Business Machines Corporation

Uttam Setty

Gaurav Saxena

Dattatreya Govindappanavar

Apoorv Kapse

Mohan Narayanswamy

Adam J Storm

Ian R Finlay

Robin Grosman

Santosh Hegde

Puneet Sharma

Embodiments of the present invention provide a method, system, and computer program product for aggregating redundant messages in a group chat. A computer may receive a plurality of messages in a group chat from one or more chat devices. The computer may extract a fact from each of the plurality of messages using natural language processing. The computer may identify redundant messages within the plurality of messages. The computer may aggregate the redundant messages into a combined message. The computer may provide the combined message to the group chat. A number of redundant messages aggregated in the combined message may be provided. The redundant messages may be provided.

Aggregating redundant messages in a group chat

A computer-implemented method includes identifying a plurality of hyperlinks on a first webpage. The computer-implemented method further includes determining, for each hyperlink in the plurality of hyperlinks, a degree of likelihood that a user will select a given hyperlink in the plurality of hyperlinks. The computer-implemented method further includes initiating a first bid request for a first ad space for a second webpage that is accessible by a first hyperlink in the plurality of hyperlinks based on the first hyperlink having a degree of likelihood above a given threshold level. The computer-implemented method further includes determining a selection of the first hyperlink by the user. The computer-implemented method further includes displaying a first advertisement associated with a first winning bid on the second webpage. A corresponding computer system and computer program product are also disclosed.

Advanced bidding for optimization of online advertising

One or more processors provide selective and piecemeal data loading and utilization. One or more processors prioritize, for loading, a data of a first data type and a data of a second data type. One or more processors generate a partially loaded data table by partially loading the data of the first data type and the data of the second data type into a table within a relational database. One or more processors utilize the partially loaded data table to execute a plurality of computing tasks.

Selective and piecemeal data loading for computing efficiency

One or more processors determine a level of data usage for two or more types of data to be loaded in a relational database. One or more processors prioritize data of the two or more types for loading. One or more processors load data of the two or more types in an order based, at least in part, on the level of data usage for the two or more types of data. One or more processors load data of the two or more types into a table within the relational database, the data being loaded in two or more portions and at times based, at least in part, on an availability of computer resources.

User-specific interesting content is determined from already buffered video content, which can be replayed to the user while the user waits for additional video content to buffer.

Intelligent replay of user specific interesting content during online video buffering

One or more processors determine a level of data usage for two or more types of data to be loaded in a database. One or more processors prioritize data of the two or more types for loading. Data of a first data type has a higher priority for loading than data of a second data type when the first data type has a higher level of data usage than the second data type. One or more processors load data of the two or more types in an order based, at least in part, on the level of data usage for the two or more types of data.

An indication to load data into a database table is received. A determination is made whether an existing set of frequency distribution statistics is available. In response to determining that an existing set of frequency distribution statistics is available, the data is loaded into the database table using the existing set of frequency distribution statistics.

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Bengaluru, India

Uttam Setty