Word detection and domain dictionary recommendation

Abstract

New word detection and domain dictionary recommendation are provided. When text content is received according to a given language, for example, Chinese language, words are extracted from the content by analyzing the content according to a variety of rules. The words then are ranked for inclusion into one or more lexicons or domain dictionaries for future use for such functionalities as text input methods, spellchecking, grammar checking, auto entry completion, definition, and the like. In addition, when a user is entering or editing text according to one or more prescribed domain dictionaries, a determination may be made as to whether more helpful domain dictionaries may be available. When entered words have a high degree of association with a given domain dictionary, that domain dictionary may be recommended to the user to increase the accuracy of the user's input of additional text and editing of existing text.

We claim: 
     
         1 . A method of recommending a domain dictionary; comprising;
 receiving a text selection from a source and displaying the text selection on a computing device;   segmenting the text selection into one or more words;   accessing one or more domain lexicons with the computing device;   comparing each of the one or more words segmented from the text selection with each of one or more words contained in the one or more domain lexicons;   ranking each of the one or more domain lexicons based on an association between each of the one or more words segmented from the text selection and one or more words contained in each of the one or more domain lexicons; and   selecting one or more of the one or more domain lexicons based on a ranking applied to the selected one or more of the one or more domain lexicons.   
     
     
         2 . The method of  claim 1 , further comprising recommending the selected one or more of the one or more domain lexicons for use with inputting or editing the text selection 
     
     
         3 . The method of  claim 1 , wherein comparing each of the one or more words segmented from the text selection with each of one or more words contained in the one or more domain lexicons includes determining a term frequency for each of the one or more words segmented from the text selection. 
     
     
         4 . The method of  claim 3 , wherein comparing each of the one or more words segmented from the text selection with each of one or more words contained in the one or more domain lexicons further includes developing a word pair for each of the one or more words segmented from the text selection with a matching word found in any of the one or more domain lexicons. 
     
     
         5 . The method of  claim 4 , wherein ranking each of the one or more domain lexicons based on an association between each of the one or more words segmented from the text selection and one or more words contained in each of the one or more domain lexicons includes ranking each of the one or more domain lexicons based on a number of word pairs developed for each of the one or more domain lexicons from words segmented from the text selection and words contained in each of the one or more domain lexicons. 
     
     
         6 . The method of  claim 1 , wherein receiving a text selection includes receiving a text input via text entry. 
     
     
         7 . The method of  claim 1 , wherein receiving a text selection includes receiving a text selection from a remote source. 
     
     
         8 . The method of  claim 1 , further comprising extracting one or more words from the text selection. 
     
     
         9 . The method of  claim 1 , wherein segmenting the text selection into one or more words includes creating a plurality of character groupings from the text selection and comparing the plurality of character groupings with one or more word lexicons for determining whether any of the plurality of character groupings is a known word. 
     
     
         10 . A system for recommending a domain dictionary; comprising;
 a plurality of word lexicons accessible with a computing device;   a new word detection engine accessible with the computing device;   a text selection from a source displayed on the computing device;   one or more words extracted from the text selection;   one or more words having been eliminated from the one or more extracted words;   a comparison of a remaining one or more extracted words to the plurality of word lexicons; and   one or more word lexicons of the plurality of word lexicons selected to include the remaining one or more extracted words based on the comparison.   
     
     
         11 . The system of  claim 10 , further comprising one or more other word lexicons of the plurality of word lexicons not selected to include the remaining one or more extracted words based on the comparison. 
     
     
         12 . The system of  claim 10 , further comprising a recommendation as a result of the comparison of at least one of the word lexicons of the plurality of word lexicons for association with one or more software functionalities associated with the computing device. 
     
     
         13 . The system of  claim 10 , wherein the text selection is text input via text entry. 
     
     
         14 . The system of  claim 10 , wherein the text selection is a text selection from a remote source. 
     
     
         15 . The system of  claim 10 , wherein the one or more eliminated words are stop words. 
     
     
         16 . The system of  claim 10 , wherein the one or more eliminated words are sub-strings of one or more other words already included in one or more of the plurality of word lexicons. 
     
     
         17 . A computer-readable medium containing computer executable instructions which when executed by a computer perform a method for recommending a domain dictionary, comprising:
 receiving a text selection;   segmenting the text selection into one or more words;   receiving one or more domain lexicons;   comparing each of the one or more words segmented from the text selection with each of one or more words contained in the one or more domain lexicons;   ranking each of the one or more domain lexicons based on an association between each of the one or more words segmented from the text selection and one or more words contained in each of the one or more domain lexicons; and   selecting one or more of the one or more domain lexicons based on a ranking applied to the selected one or more of the one or more domain lexicons.   
     
     
         18 . The computer-readable medium of  claim 17 , further comprising recommending the selected one or more of the one or more domain lexicons for use with inputting or editing the text selection. 
     
     
         19 . The computer-readable medium of  claim 17 , wherein comparing each of the one or more words segmented from the text selection with each of one or more words contained in the one or more domain lexicons includes determining a term frequency for each of the one or more words segmented from the text selection. 
     
     
         20 . The computer-readable medium of  claim 19 , wherein comparing each of the one or more words segmented from the text selection with each of one or more words contained in the one or more domain lexicons further includes developing a word pair for each of the one or more words segmented from the text selection with a matching word found in any of the one or more domain lexicons.