International Business Machines Corporation

Jun Yi Du

Yue Liu

Chuan Yang Wang

Yu Xin Zhao

Xiao F Wang

Rui Shi

Guang Shi

Wei Lin C W Wu

Luo Xu Min

Jian C D L Zhang

Prioritizing resource allocation to computer applications which includes: grouping the computer applications into groups according to an initial criteria; modifying the groups according to one or more criteria used to identify active computer applications; analyzing the groups to prioritize the groups in order of the active time of the computer applications in the groups; analyzing the computer applications in the groups to prioritize the computer applications in the groups in order of the active time of the computer applications in the groups; setting the highest priority for the computer applications that either (1) have high frequency of use, or (1) are active now; and prioritizing the computer applications according to the priority setting.

Self-adjusting system for prioritizing computer applications

A computer provides search suggestions by capturing data from a first application, wherein the data includes data displayed on a screen by the first application. The computer segments the data from the first application into blocks. The computer extracts words from the data from the first application. The computer generates tokens of phrases and words using natural language processing tokenization. The computer scores the blocks based upon the data from the first application. The computer scores the tokens based upon the scoring of the blocks and the data from the first application. The computer detects a switch action from the first application to a second application, wherein the second application contains a search function. The computer provides the scored tokens to the search function of the second application.

Generating search keyword suggestions from recently used application

Methods, computer program products, and system are presented. The methods include, for instance: identifying, by one or more processor, a current task, obtaining, by the one or more processor, an indicator of a commencement of a switching event, where the switching event includes a transition originating from the current task and concluding at a new task, obtaining, by the one or more processor, behavior analysis data relating to a plurality of past switching events, where each past switching event includes a transition originating from the current task and concluding at a target task. The behavior analysis data includes a timestamp for each past switching event. The method also includes determining, by the one or more processor, based on the behavior analysis data, at least one recommended task, where the at least one recommended task includes at least one target task.

Intellective switching between tasks

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Ningbo, China

Jun Yi Du