Our patent gurus have discovered an interesting patent filing from Google that could reveal the applications they are planning for the Google mobile phones. Alternatively this technology could even debut in the iPhone when it is released in June.
Google has become the number one place we go when we want to find something online and the Mountain View based company has been building mobile versions of common applications such as Gmail and Google Maps/Local for some time now.
The patent filing details an application that can predict what a user is searching for or the words they are typing in a text message by taking into account the users location, previous searching / messaging history and even the time of day.
This concept might seem familiar to older Google users. Way back in 2000 an April Fools joke called Google MentalPlex promised to use 1.6 billion variables to predict what you wanted before you searched. Another ongoing project used in Google Labs and the latest Google Toolbar predicts what you are searching for as you type but still doesnâ€™t go anywhere near as far as the Nonstandard locality-based text entry patent filed in 2005.
In the patent Google discusses how all the data is stored on Googleâ€™s servers and queries are sent whenever the user is searching for something or typing a message. Presumably the queries would be sent over some kind of mobile AJAX interface.
This patent is truly groundbreaking in what the application could do. Imagine that you are planning a night out in London. At 6pm Google could predict you are looking for a restaurant and, given your history of looking for directions to Chinese restaurants every week, would select an array of suitable places for you to eat.
At 9pm you would turn your phone on again and Google would know you wanted bars near the restaurant. At 11pm Google again predicts you need a list of local taxi firms.
In one aspect, a computer-implemented method of providing text entry assistance data is disclosed. The method includes receiving at a system location information associated with a user, receiving at the system information indicative of predictive textual outcomes, generating dictionary data using the location information, and providing the dictionary data to a remote device. The received information indicative of predictive textual outcomes may relate to search requests made by a plurality of remote searchers. Also, the dictionary data may include a plurality of terms with a corresponding plurality of predictive weightings, and dictionary data may be generated using the information indicative of predictive textual outcomes).
 In one implementation, providing the dictionary data to the remote device may include transmitting the data to a mobile phone. The system may also receive user preferences that are used in searching based on the search results. The generating of the dictionary data may also include producing data related to the information indicative of the user location. The generated dictionary data may be associated with places near the user location. Also, the generated dictionary data may be associated with common query data from users near the user location, and may be provided to the remote device in response to a request from the remote device. The dictionary data may also be compressed before it is provided to the remote device, and the data may include supplemental data for addition to a preexisting dictionary on the remote device.
 In another implementation, the method may further include receiving a search request, generating a search result, and providing the search result along with the dictionary data. The dictionary data may include data from documents relating to the search result. In addition, the dictionary data may include data corresponding to one or more areas in the proximity of the user location, which may in turn comprise location names.
 In another aspect, a data collection and distribution system is provided and includes a request processor to receive data requests from one or more remote clients, a local search engine to search in response to the data requests, a dictionary generator to produce information for use by the one or more clients containing predictive data entry information for the one or more clients, and a response formatter to receive information responsive to the data requests including predictive data entry information, and provide the information responsive to the data requests for use by the one or more clients. The request processor may be operable to receive information indicative of a user location. Also, the local search engine may be operable to extract information indicative of a user location from the data requests.
In one implementation, the dictionary generator may include a concurrence rater that calculates predicted concurrence scores for a plurality of objects, and the plurality of objects may include a plurality of terms that may be entered by a user in generating a data request. The system may also include an object selector to identify objects in a document for submission to the concurrence rater. The local search engine may also be operable to receive a plurality of requests and information indicative of a user location and provide the requests for transmission by the response formatter along with predictive data entry information. The information for use by the one or more clients may include data corresponding to one or more areas in the proximity of the user location, which may in turn comprise location names.
 In yet another aspect, a computer-implemented system for providing information indicative of probable usage of objects by the user of a data entry device may include means for providing documents associated with a user location and indicative of usage by a user or users, a concurrence rater to analyze the documents for usage data of objects in the documents and to generate associated concurrence ratings, and an interface to transmit the concurrence ratings to a data entry device. The concurrence rater may further analyze the documents for location data of the objects and generates concurrence ratings, and the concurrence ratings may be at least partially based on how far a location associated with the location data of the object is from the user location. Also, the concurrence ratings may be at least partially based on preferences of a user.
 In another aspect, a communication device includes a transceiver to receive and transmit information. The transmitted information includes information indicative of a user location. The device also includes a vocabulary repository containing information indicative of the probable intended usage of ambiguous information entered by a user of the device, the occurrence data reflecting an association of the user location with the information indicative of the probable intended usage, and a disambiguation engine to resolve the ambiguous information provided to the device to a probable solution by identifying possible solutions and to apply the information indicative of probable intended usage to the possible solutions.
 In one implementation, the system may further include a positioning system used to obtain the information indicative of the user location. Also, a user may input the information indicative of the user location.
 In another implementation, the preferences of a user may determine what information is contained in the vocabulary repository. Also, the indicative information associated with the occurrence data may be eliminated from the vocabulary repository when the occurrence data reaches a certain threshold. The occurrence data may contain data that represents usage practices by members of a demographic group.
Discovered by John from Gas Fires & Electric Fires Galore.