In the very near future , you can do a search on Google without bothering to knock or say a query . Instead, you can just shake your phone , or hold a button in a certain period of time , and tell your phone something like "search now - looking for now." Called looking parameterless , this kind of search may depend on the context of the search is done . So you have to understand what is parameterless search now?
Context is very important in Google's search parameterless
For example , imagine that the system is working with speed 50mph , and you shake your phone . It tells you that there is congestion ahead , and it provides the route ( route ) instead. Or it shows you a map with traffic information coding for nearby areas vary according to access conditions . Or , you can have an appointment with a client is done via email that in your schedule , and you want to find and test email to ensure that you have the right phone number . It can display number and offer to make calls on your behalf . If you regularly train at about 8:00 in the morning during the week , shake your phone at 7:50 am can enable a real-time schedule for the railroad .
Contextual information for a parameterless searches can include things like :
- Information Date / Time ,
- Geographic location information ,
- Information schedule ,
- Information rate of speed , and
- Device Information operations ( like sending emails for different purposes ) .
Patent is :
Provide results to search queries not parameterless
Invented by Sumit Agarwal , Vic Gundotra , Alex Nicolaou
Assigned to Google
U.S. Patent 8,478,519
Level July 2, 2013
Filed August 30, 2010
Contextual information could include more specific things like :
- Geographic location ,
- Weather conditions ,
- Corporate nearby ,
- The volume of background noise ,
- The level of ambient light ,
- An image captured by camera mobile devices ,
- The rate of speed of travel,
- Time and date information ,
- Schedules appointments ,
- Activity Recent users ,
- Activity frequent users .
Current context can be defined by the sensor data and local or even remote device for mobile computing . For example , traffic speeds and congestion can be identified by the sensors in the phone on the road ahead .
If anyone watched the news content is developed through their browser or a news app , and have watched a few times , parameterless search can help to see updates to such content .
If someone is driving down the road , and here's a news story , a parameterless query can cause reactions with both.
This system is self-training , and can learn about the different types of information that you might be interested in , based on context . For example , if the query results of a parameterless end displays a list of local restaurants , and you end up choosing one of them and drive there , the system knows that in the context of so, a set of outcomes restaurant is a proper response ( and it can learn about your taste in food ) . It can learn about user actions such as :
For example , if a user is provided with an update on a blog recently that regular users read and send users a link to the blog post to be updated to his friends , who use send the link can be recorded as user behavior data in the data repository user behavior of mobile computing devices and use to provide search results to the search request parameterless in the future .
Patent tell us approach the search query is not limited to parameterless mobile phone , can work with tablets , laptops , car navigation systems , digital assistant some individuals , or desktop .