Abstract: A method and an apparatus for determining a morpheme importance analysis model is provided, which belongs to the field of computers. The method includes: acquiring at least two pieces of training data, each piece of training data including a query, any morpheme in the query, and an importance score of the any morpheme in the query; determining a feature value of each preset feature of each piece of training data; and determining a model parameter according to the feature value of each preset feature of all training data and importance scores of morphemes included in all training data, and determining a morpheme importance analysis model according to the determined model parameter.

Abstract: An information processing method, a server, and a computer storage medium are disclosed. The method includes: obtaining first information from a first terminal, the first information including at least information content and an information presentation style parameter; obtaining second information from the second terminal, the second information including at least basic user information and/or user behavior information and/or user relationship chain information; generating sampling information according to the first information and the second information, and constructing, according to the sampling information, at least one processing policy that separately corresponds to a first type of processing node interacting with the first terminal and a second type of processing node interacting with the second terminal; and generating the third information according to the first information and the at least one processing policy, and sending the third information to the second terminal for information presentation.

Abstract: The disclosed system provides an improved method for text input by using linguistic models based on conditional probabilities to provide meaningful word completion suggestions based on previously entered words. The system uses previously entered n-grams, where n>=2, to generate a list of candidate words matching a current user input. The candidate words are based on one or more conditional probabilities, where the conditional probabilities show a probability of a candidate word following a previously entered n-gram. The system displays the list of candidate words to the user and allows the user to select a desired word for entry. The system also utilizes the context of the text entry to select the candidate words.

Abstract: A method and an apparatus for determining a morpheme importance analysis model is provided, which belongs to the field of computers. The method includes: acquiring at least two pieces of training data, each piece of training data including a query, any morpheme in the query, and an importance score of the any morpheme in the query; determining a feature value of each preset feature of each piece of training data; and determining a model parameter according to the feature value of each preset feature of all training data and importance scores of morphemes included in all training data, and determining a morpheme importance analysis model according to the determined model parameter.

Abstract: A method and apparatus for clustering search terms are provided by the present invention. The method includes: A, establishing a candidate search term set, wherein the candidate search term set comprises a first search term provided by a user, and a second search term related to the first search term; B, performing a clustering operation on the first search term and the second search term related to the first search term in the candidate search term set according to text characteristic and/or semantic characteristic of search term. The accuracy and relevance of search term clustering can be improved by use of the method.