Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to implement automated responses to data representing electronic messages, among other things, and, more specifically, to a computing and data platform that implements logic to facilitate implementation of an automated predictive response computing system being configured to implement, for example, an automated predictive response engine configured to access internal (e.g., in-conversation) data and external (e.g., extra-conversation) data to predictively generate automated responses, such as assisting an agent or an agent computing device, among other things. In an example, a method may include forming identified features, determining a first predicted response, computing a second predicted response as a function of an identified feature, and presenting data as user inputs in a user interface portion to include a first predicted response and a second predicted response as a predicted response.

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: receive a string used to search an available domain name, identify a token within the string including a unigram, and generate and transmit one or more available domain name candidates including a unigram and one or more tokens interchangeable with a token previously co-occurring with the unigram token.

A method and system are described that provide responses to natural language queries regarding the performance of a business. The method and system provide for crowd-sourced data to determine natural language query suggestions to transmit to a user, based upon previously submitted questions of the user and/or similar merchants to the user. Natural language query suggestions may be provided as utterances to a keyboard of a merchant user. The merchant user may select one or more suggestions provided. The use of natural language queries and responses allows a merchant without a business intelligence background to obtain business insights easily and accurately assess his performance (e.g., against similar merchants, etc.) without personally identifiable or confidential information of other merchants being compromised.

A computer-implemented method is provided for suggesting a query term. The method includes obtaining a seed term and a candidate term. The method further includes retrieving two nodes indicating the seed term and the candidate term respectively from a semi-structured corpora. The method also includes determining, by a processor device, whether the candidate term includes details of information on the seed term based on a positional relation between the two nodes in the semi-structured corpora. The method additionally includes suggesting the candidate term as an additional query term in response to a positive determination. The method further includes performing the query with the candidate term as the additional query term in response to a suggestion of use acceptance to enhance query answer retrieval results.

The present disclosure relates to methods and systems for controlling content distribution. The methods and systems receive an original search query and expand the original search query by adding one or more neutral words to create an expanded search query. The methods and systems automatically classify the original search query using the expanded search query in an accurate manner and use the classification to control content distribution.

An information processing apparatus includes a memory and at least one processor. The memory stores a learned model having learned correlation between character strings included in a search history of words and/or phrases. The processor inputs information of a search history of words and/or phrases by a target user to the learned model. The processor creates a word and/or a phrase for learning by the target user.

In various embodiments, a natural language (NL) application receives a first incomplete natural language (NL) request, and generates one or more request completion recommendations based on at least the first incomplete NL request and a first recommendation model, where the first recommendation model is generated via a machine learning algorithm applied to a first data dependency model and a first request completion model. The NL application receives a selection of a first request completion recommendation included in the one or more request completion recommendations, generates a complete request based on the first incomplete NL request and the first request completion recommendation, and causes the complete request to be applied to the data storage system.

The present application discloses a method for building a ranking model, a query auto-completion method and corresponding apparatuses, which relates to the technical field of intelligent search. An implementation includes: acquiring from a POI query log a query prefix input when a user selects a POI from query completion suggestions, POIs in the query completion suggestions corresponding to the query prefix and the POI selected by the user in the query completion suggestions; constructing positive and negative example pairs using the POI selected by the user and the POIs not selected by the user in the query completion suggestions corresponding to the same query prefix; and performing a training operation using the query prefix and the positive and negative example pairs corresponding to the query prefix to obtain the ranking model.

A system for providing reactive suggestions to text queries is provided comprising computer, client device, and application on the computer. The system receives notification of entry of a partial text string into a field of a client device. The system also accesses stored records describing behaviors and tendencies of a user of when previously accessing applications, functionalities, and data. The system also generates associations between the partial string and stored records, the associations describing linkages of the string with behaviors and tendencies described in the records. The system also ranks the associations by likelihood of matching the text string. The system also presents a first choice to the client device based on the rankings, the first choice when accepted by the client device invoking a first action suggested by the highest-ranked association. Based on receipt of the first choice, the system causes the client device to invoke the first action.

Method, system, and programs for providing enhanced search term suggestions. A set of incomplete search terms indicating a sequence of search terms entered may be received. It may be detected that the sequence contains a descending phase followed by an ascending phase. In response to the detection, a pair of misinput term and corresponding corrected term may be identified in the set of incomplete search terms. A probability with respect to the misinput term is a misinput of the corresponding corrected term may be determined based on a historical context. Using such a probability, an incomplete search term containing the misinput term may be corrected. One or more proposed search terms may be determined based on the corrected incomplete search term for suggestion to the user.