Abstract: A method for detecting data in a sequence of characters or text using both a statistical engine and a pattern engine. The statistical engine is trained to recognize certain types of data and the pattern engine is programmed to recognize the grammatical pattern of certain types of data. The statistical engine may scan the sequence of characters to output first data, and the pattern engine may break down the first data into subsets of data. Alternatively, the statistical engine may output items that have a predetermined probability or greater of being a certain type of data and the pattern engine may then detect the data from the output items and/or remove incorrect information from the output items.

Abstract: A method of processing a sequence of characters, the method comprising converting the sequence of characters into a sequence of tokens so that each token comprises a lexeme and one of a plurality of token types. Each of the plurality of token types relates to at least one of a plurality of predetermined functions, wherein at least one said token type relates to multiple functions of the plurality of predetermined functions.

Abstract: An apparatus for processing a sequence of tokens to detect predetermined data, wherein each said token has a token type, and the predetermined data has a structure that comprises a predetermined sequence of token types, including at least one optional token type. The apparatus comprises a processor arranged to: provide a tree for detecting the predetermined data, the tree comprising a plurality of states, each said state being linked with at least one other state by a respective condition, the arrangement of linked states forming a plurality of paths; and compare the token types of the sequence of tokens to respective conditions in the tree to match the sequence of tokens to one or more paths in the tree, wherein the predetermined data can be detected without using an epsilon reduction to take account of said at least one optional token type.

Abstract: A method of processing a sequence of characters, the method comprising converting the sequence of characters into a sequence of tokens so that each token comprises a lexeme and one of a plurality of token types. Each of the plurality of token types relates to at least one of a plurality of predetermined functions, wherein at least one said token type relates to multiple functions of the plurality of predetermined functions.

Abstract: A method of processing a sequence of characters, the method comprising converting the sequence of characters into a sequence of tokens so that each token comprises a lexeme and one of a plurality of token types. Each of the plurality of token types relates to at least one of a plurality of predetermined functions, wherein at least one said token type relates to multiple functions of the plurality of predetermined functions.

Abstract: A method for detecting data in a sequence of characters or text using both a statistical engine and a pattern engine. The statistical engine is trained to recognize certain types of data and the pattern engine is programmed to recognize the grammatical pattern of certain types of data. The statistical engine may scan the sequence of characters to output first data, and the pattern engine may break down the first data into subsets of data. Alternatively, the statistical engine may output items that have a predetermined probability or greater of being a certain type of data and the pattern engine may then detect the data from the output items and/or remove incorrect information from the output items.

Abstract: A method for detecting data in a sequence of characters or text using both a statistical engine and a pattern engine. The statistical engine is trained to recognize certain types of data and the pattern engine is programmed to recognize the grammatical pattern of certain types of data. The statistical engine may scan the sequence of characters to output first data, and the pattern engine may break down the first data into subsets of data. Alternatively, the statistical engine may output items that have a predetermined probability or greater of being a certain type of data and the pattern engine may then detect the data from the output items and/or remove incorrect information from the output items.

Abstract: An apparatus for processing a sequence of tokens to detect predetermined data, wherein each said token has a token type, and the predetermined data has a structure that comprises a predetermined sequence of token types, including at least one optional token type. The apparatus comprises a processor arranged to: provide a tree for detecting the predetermined data, the tree comprising a plurality of states, each said state being linked with at least one other state by a respective condition, the arrangement of linked states forming a plurality of paths; and compare the token types of the sequence of tokens to respective conditions in the tree to match the sequence of tokens to one or more paths in the tree, wherein the predetermined data can be detected without using an epsilon reduction to take account of said at least one optional token type.

Abstract: A method for detecting data in a sequence of characters or text using both a statistical engine and a pattern engine. The statistical engine is trained to recognize certain types of data and the pattern engine is programmed to recognize the grammatical pattern of certain types of data. The statistical engine may scan the sequence of characters to output first data, and the pattern engine may break down the first data into subsets of data. Alternatively, the statistical engine may output items that have a predetermined probability or greater of being a certain type of data and the pattern engine may then detect the data from the output items and/or remove incorrect information from the output items.

Abstract: A graphical user interface (GUI) is disclosed. The GUI comprises a three-dimensional virtual desktop surface. The GUI displays a view of the three-dimensional virtual desktop surface from a selected viewpoint and viewing angle and modifies at least one of the viewpoint and viewing angle based on detected head movements of a user.

Abstract: An apparatus for processing a sequence of tokens to detect predetermined data, wherein each said token has a token type, and the predetermined data has a structure that comprises a predetermined sequence of token types, including at least one optional token type. The apparatus comprises a processor arranged to: provide a tree for detecting the predetermined data, the tree comprising a plurality of states, each said state being linked with at least one other state by a respective condition, the arrangement of linked states forming a plurality of paths; and compare the token types of the sequence of tokens to respective conditions in the tree to match the sequence of tokens to one or more paths in the tree, wherein the predetermined data can be detected without using an epsilon reduction to take account of said at least one optional token type.

Abstract: A method of processing a sequence of characters, the method comprising converting the sequence of characters into a sequence of tokens so that each token comprises a lexeme and one of a plurality of token types. Each of the plurality of token types relates to at least one of a plurality of predetermined functions, wherein at least one said token type relates to multiple functions of the plurality of predetermined functions.