Browse Prior Art Database

Method of providing auto-complete candidates Disclosure Number: IPCOM000250369D
Publication Date: 2017-Jul-06
Document File: 3 page(s) / 93K

Publishing Venue

The Prior Art Database

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 53% of the total text.

Method of providing auto-complete candidates


Disclosed is a method of providing more useful autocomplete candidates by capturing and analyzing user input, history information, context information as well as dynamically analyzed result. The dynamically analyzed result includes information captured by smart tools, including using camera to recognize the area where user's eyes focus on previously, and furthermore to collect the text on these area as candidate with high priority. After analyzing these candidates, our idea is to filter and sort these candidates to provide most useful autocomplete candidate list. This is a cognitive forecast.

Description It is quite often to type the full sentence, especially when typing full command line in the console. Autocomplete is quite useful to help type full command line. For example, the Bash shell has this sweet feature where you can use the TAB (tabulator) key to auto-complete certain things. Although there is some plug-in to predefine additional dictionary for autocomplete, there is still gap to autofill necessary information. One simple case is that we want to kill one process. First, we use "ps" to get process id, and then we need to copy process id to next command line for kill. This is not convenient. Advantage: 1. provide system and method to generate smarter autocomplete candidate list; 2. providing useful candidate list which is not only based on current context, and information from plug-in, but also based on history information and dynamically analyzed information. 3. candidate list is sorted according to user's use case so that useful candidate can be easily found Below is overview of how our invention works.

a. collect user input and save as key parameter for matcher b. generate available candidate autocomplete list by consolidating 1). history information which was saved in history information repository 2). context information, such as user environment information, interactive session information, etc. 3). dynamically analyzed information c. match user input and available candidate autocomplete list d. use candidate sorter to sort "filtered candidate autocomplete list" e. provide candidate to user for autocomplete For dynamically analyzed information, below picture shows the basic concept to capture the focus area of users' eyes. And the text in focused are will be collected and analyzed as input for candidate consolidation. Matcher detail about how the matcher works and the logic what make sense to store. a)For the history information, it contains following information in the past:

• user input • dynamically analyzed information • the output on the screen

• the output on the screen that last for several seconds • the output on the editor (E.g. vi or visual editor) • user specified documents

The above items are selectable, user can decide which can be st...