Abstract: Techniques are provided for training, by a system operatively coupled to a processor, an attention weighted recurrent neural network encoder-decoder (AWRNNED) using an iterative process based on one or more paragraphs of agent sentences from respective transcripts of one or more conversations between one or more agents and one or more customers, and based on one or more customer response sentences from the respective transcripts, and generating, by the system, one or more groups respectively comprising one or more agent sentences and one or more customer response sentences selected based on attention weights of the AWRNNED.

Abstract: Techniques are provided for training, by a system operatively coupled to a processor, an attention weighted recurrent neural network encoder-decoder (AWRNNED) using an iterative process based on one or more paragraphs of agent sentences from respective transcripts of one or more conversations between one or more agents and one or more customers, and based on one or more customer response sentences from the respective transcripts, and generating, by the system, one or more groups respectively comprising one or more agent sentences and one or more customer response sentences selected based on attention weights of the AWRNNED.

Abstract: Techniques are provided for training, by a system operatively coupled to a processor, an attention weighted recurrent neural network encoder-decoder (AWRNNED) using an iterative process based on one or more paragraphs of agent sentences from respective transcripts of one or more conversations between one or more agents and one or more customers, and based on one or more customer response sentences from the respective transcripts, and generating, by the system, one or more groups respectively comprising one or more agent sentences and one or more customer response sentences selected based on attention weights of the AWRNNED.

Abstract: A method, apparatus and system for processing webpage data. The method includes: in response to a webpage being opened, sending a link contained in the webpage to a network side device; receiving a group identification from the network side device, the group identification being determined by the network side device according to the link and used to specify a group the link belongs to; determining whether there is a browsed link belonging to the group specified by the group identification; and in response to determining there is a browsed link belonging to the group specified by the group identification, prompting that webpage content pointed by the link contained in the webpage has been browsed.

Abstract: This disclosure provides a computer-implemented method. The method may include extracting one or more features based on a first utterance from a first interlocutor in a dialog and a second utterance from a second interlocutor in the dialog. The method may further include inferring one or more personality traits of the first interlocutor based on the one or more extracted features from the dialog.

Abstract: Embodiments of the invention provide a computer-implemented method, computing system and computer program product for analyzing a message in a social network. The method comprises identifying an entity from the message; detecting historical popularity of the entity in a social network; identifying a topic from the message; detecting historical popularity of the topic in the social network; and generating an entity-topic correlation factor for the entity and the topic based on the historical popularity of the entity and the historical popularity of the topic. Results obtained with embodiments of the invention may be provided to popularity prediction tools for improving popularity prediction of messages in social networks.

Abstract: This disclosure provides a computer-implemented method. The method may include generating one or more features based on a first utterance from a first interlocutor in a dialog and a second utterance from a second interlocutor in the dialog.

Abstract: Techniques are provided for training, by a system operatively coupled to a processor, an attention weighted recurrent neural network encoder-decoder (AWRNNED) using an iterative process based on one or more paragraphs of agent sentences from respective transcripts of one or more conversations between one or more agents and one or more customers, and based on one or more customer response sentences from the respective transcripts, and generating, by the system, one or more groups respectively comprising one or more agent sentences and one or more customer response sentences selected based on attention weights of the AWRNNED.

Abstract: Embodiments of the invention provide a computer-implemented method, computing system and computer program product for analyzing a message in a social network. The method comprises identifying an entity from the message; detecting historical popularity of the entity in a social network; identifying a topic from the message; detecting historical popularity of the topic in the social network; and generating an entity-topic correlation factor for the entity and the topic based on the historical popularity of the entity and the historical popularity of the topic. Results obtained with embodiments of the invention may be provided to popularity prediction tools for improving popularity prediction of messages in social networks.

Abstract: A mechanism is provided for personalizing a user's E-commerce environment. Identified lifecycle state transactions associated with the user are modeled by performing a lifecycle state transition probability calculation utilizing collected social media data and transaction data. Utilizing the model of the identified lifecycle state transactions, a two-level Hidden Markov Model (HMM) lifecycle model is generated for current lifecycle states being experienced by the user. Utilizing the two-level HMM lifecycle model for current lifecycle states being experienced by the user, one or more future behavioral predictions are generated with regard to the user's lifecycle. One or more E-commerce recommendations are then issued to the user based on the one or more future behavioral predictions.

Abstract: Business application logic corresponding to a business is generated according to requirements of the business. The business application logic includes Web services and Widgets. The Widgets in the business application logic are mashed up to create a Widget mashup application. An adaptation relationship is established between the Web services and the Widgets in the Widget mashup application. An executable business process is generated for the business based on the business application logic and the adaptation relationship. An executable mashup Widget application is generated based on the Widget mashup application and the adaptation relationship.

Abstract: A method, apparatus and system for processing webpage data. The method includes: in response to a webpage being opened, sending a link contained in the webpage to a network side device; receiving a group identification from the network side device, the group identification being determined by the network side device according to the link and used to specify a group the link belongs to; determining whether there is a browsed link belonging to the group specified by the group identification; and in response to determining there is a browsed link belonging to the group specified by the group identification, prompting that webpage content pointed by the link contained in the webpage has been browsed.

Abstract: Business application logic corresponding to a business is generated according to requirements of the business. The business application logic includes Web services and Widgets. The Widgets in the business application logic are mashed up to create a Widget mashup application. An adaptation relationship is established between the Web services and the Widgets in the Widget mashup application. An executable business process is generated for the business based on the business application logic and the adaptation relationship. An executable mashup Widget application is generated based on the Widget mashup application and the adaptation relationship.