Abstract: Disclosed are a method and system for intelligent source tracing of organic pollution of a water body, which belongs to the technical field of environmental analytical chemistry. The method comprises: acquiring organic matter analysis and detection data from water samples of a polluted water body through high performance liquid chromatography-tandem mass spectrometry; performing high-throughput screening on the organic matter in the water samples according to said data to determine pollutants; identifying pollution sources by means of network analysis according to the determined pollutants; and according to the identified pollution sources and the organic pollutants, determining key pollutants and quantifying the pollution contributions thereof by using a machine learning classification model.

Abstract: Disclosed are a method and system for intelligent source tracing of organic pollution of a water body, which belongs to the technical field of environmental analytical chemistry. The method comprises: acquiring organic matter analysis and detection data from water samples of a polluted water body through high performance liquid chromatography-tandem mass spectrometry; performing high-throughput screening on the organic matter in the water samples according to said data to determine pollutants; identifying pollution sources by means of network analysis according to the determined pollutants; and according to the identified pollution sources and the organic pollutants, determining key pollutants and quantifying the pollution contributions thereof by using a machine learning classification model.

Abstract: A method includes the following: creating trunk status data for each user account, in response to detecting a plurality of concurrent access sessions relating to a single user account, creating respective branch status data for each access session; updating the branch status data in accordance with user access operations; and when an access session relating to a user account ends, updating the trunk status data for said user account based on a comparison of the branch status data of the access session which has ended with the trunk status data for said user account.

Abstract: A method for an app search engine leveraging user reviews is provided. The method includes receiving an app search query from a user, determining a plurality of relevant apps based on the received app search query, and extracting app descriptions and user reviews associated with the plurality of relevant apps from an app database. The method also includes preprocessing the extracted app descriptions and user reviews of each of the plurality of relevant apps to generate a text corpus and creating a topic-based language model for each of the plurality of relevant apps based on the generated text corpus. Further, the method includes ranking a list of relevant apps using the topic-based language model and providing the ranked app list for the user.

Abstract: The present disclosure includes: establishing, by a network management system (NMS), a network configuration protocol (NETCONF) configuration template library including a plurality of configuration templates, based on a network configuration protocol (NETCONF). Each configuration template includes a type of a network device which supports the NETCONF, transport layer protocols which are supported by the network device, and configuration parameters corresponding to each of the transport layer protocols to set up NETCONF sessions of the network device. In response to a network device joining the NMS, searching the NETCONF configuration template library to find a matching NETCONF configuration template which matches a type of the network device which has joined the NMS. Establishing a NETCONF session with the network device which has joined the NMS, based on a transport layer protocol and corresponding configuration parameters of the matching NETCONF configuration template.

Abstract: Searching, according to the type information of a network device, for a transport layer protocol supported by the network device in a transport layer architecture of a network configuration protocol (NETCONF) configuration framework and definition information which is to be used to implement a connection to the network device. Establishing a NETCONF session to the network device by using the transport layer protocol and the definition information. During establishment of the NETCONF session, comparing a first NETCONF capability set obtained from the network device with a second NETCONF capability set which is supported by the NMS and is defined in a metadata definition file. Assigning an intersection of the first NETCONF capability set and the second NETCONF capability set as an active capability set. Then, performing a network configuration access to the network device based on the active capability set.

Abstract: In accordance with some embodiments of the disclosed subject matter, a method and a system for App page recommendation are provided. The method includes: based on social media contents generated by a user, establishing a parallel corpora comprising an implicit query database including a plurality of user implicit query texts, and an explicit query database including a plurality of user explicit query texts, wherein the plurality of user implicit query texts correspond to the plurality of user explicit query texts; receiving a voice user query from the user; converting the voice user query to a text query; extracting implicit intent text from the text query; inferring a user intent using the parallel corpora based on the extracted implicit intent text; ranking a plurality of App pages according to the inferred user intent; and recommending a subset of the plurality of App pages to the user based on the ranking.

Abstract: A method for scalable user intent mining is provided. The method includes detecting named entities from a plurality of query logs in a public query log dataset and generating features of the plurality of query logs based on the detected named entities. The method also includes applying a multimodal restricted boltzmann machine (RBM) on the generated features of the plurality of query logs to train a public multimodal RBM and generating a plurality of public query representations. Further, the method includes receiving a search query from a user, determining whether there are a plurality of history queries of the user. When there is no history query, user intent is predicted using the public multimodal RBM. When there are the history queries, the public multimodal RBM is applied on the plurality of history queries to train a personalized multimodal RBM, and the user intent is predicted using the personalized multimodal RBM.

Abstract: A method for multimodal clue based personalized app function recommendation is provided. The method includes receiving an app search query from a user, obtaining a plurality of real-time clues collected from the user and extracting a plurality of features to represent the collected clues, wherein the plurality of features include structured features and text features. The method also includes generating a joint representation of the multimodal clues based on the plurality of extracted features and creating a logistic regression model based on the joint representation of the multimodal clues. Further, the method includes ranking a list of app functions using the logistic regression model and displaying the ranked app function list for the user.

Abstract: In accordance with some embodiments of the disclosed subject matter, a method and a system for App page recommendation are provided. The method includes: based on social media contents generated by a user, establishing a parallel corpora comprising an implicit query database including a plurality of user implicit query texts, and an explicit query database including a plurality of user explicit query texts, wherein the plurality of user implicit query texts correspond to the plurality of user explicit query texts; receiving a voice user query from the user; converting the voice user query to a text query; extracting implicit intent text from the text query; inferring a user intent using the parallel corpora based on the extracted implicit intent text; ranking a plurality of App pages according to the inferred user intent; and recommending a subset of the plurality of App pages to the user based on the ranking.

Abstract: A method includes the following: creating trunk status data for each user account, in response to detecting a plurality of concurrent access sessions relating to a single user account, creating respective branch status data for each access session; updating the branch status data in accordance with user access operations; and when an access session relating to a user account ends, updating the trunk status data for said user account based on a comparison of the branch status data of the access session which has ended with the trunk status data for said user account.

Abstract: The present disclosure provides a time-value estimation method for sharing environment, including obtaining time-values of a plurality of shared items from a sharing platform. A time-value is a time duration for the shared item to be shared or traded. Further, a plurality of features of the plurality of shared items from the sharing platform may be extracted. The features may include objective-level features related to a specific item and subjective-level features related to an owner of the specific item. A time-value model may be trained to obtain a time-value estimation function based on the time-values of the plurality of shared items and the plurality of features of the plurality of shared items. The method may further include estimating a time-value of an item in the sharing platform based on the plurality of features of the item and the time-value estimation function.

Abstract: A method for multimodal clue based personalized app function recommendation is provided. The method includes receiving an app search query from a user, obtaining a plurality of real-time clues collected from the user and extracting a plurality of features to represent the collected clues, wherein the plurality of features include structured features and text features. The method also includes generating a joint representation of the multimodal clues based on the plurality of extracted features and creating a logistic regression model based on the joint representation of the multimodal clues. Further, the method includes ranking a list of app functions using the logistic regression model and displaying the ranked app function list for the user.

Abstract: Searching, according to the type information of a network device, for a transport layer protocol supported by the network device in a transport layer architecture of a network configuration protocol (NETCONF) configuration framework and definition information which is to be used to implement a connection to the network device. Establishing a NETCONF session to the network device by using the transport layer protocol and the definition information. During establishment of the NETCONF session, comparing a first NETCONF capability set obtained from the network device with a second NETCONF capability set which is supported by the NMS and is defined in a metadata definition file. Assigning an intersection of the first NETCONF capability set and the second NETCONF capability set as an active capability set. Then, performing a network configuration access to the network device based on the active capability set.

Abstract: The present disclosure includes: establishing, by a network management system (NMS), a network configuration protocol (NETCONF) configuration template library including a plurality of configuration templates, based on a network configuration protocol (NETCONF). Each configuration template includes a type of a network device which supports the NETCONF, transport layer protocols which are supported by the network device, and configuration parameters corresponding to each of the transport layer protocols to set up NETCONF sessions of the network device. In response to a network device joining the NMS, searching the NETCONF configuration template library to find a matching NETCONF configuration template which matches a type of the network device which has joined the NMS. Establishing a NETCONF session with the network device which has joined the NMS, based on a transport layer protocol and corresponding configuration parameters of the matching NETCONF configuration template.

Abstract: A method for an app search engine leveraging user reviews is provided. The method includes receiving an app search query from a user, determining a plurality of relevant apps based on the received app search query, and extracting app descriptions and user reviews associated with the plurality of relevant apps from an app database. The method also includes preprocessing the extracted app descriptions and user reviews of each of the plurality of relevant apps to generate a text corpus and creating a topic-based language model for each of the plurality of relevant apps based on the generated text corpus. Further, the method includes ranking a list of relevant apps using the topic-based language model and providing the ranked app list for the user.

Abstract: A method for scalable user intent mining is provided. The method includes detecting named entities from a plurality of query logs in a public query log dataset and generating features of the plurality of query logs based on the detected named entities. The method also includes applying a multimodal restricted boltzmann machine (RBM) on the generated features of the plurality of query logs to train a public multimodal RBM and generating a plurality of public query representations. Further, the method includes receiving a search query from a user, determining whether there are a plurality of history queries of the user. When there is no history query, user intent is predicted using the public multimodal RBM. When there are the history queries, the public multimodal RBM is applied on the plurality of history queries to train a personalized multimodal RBM, and the user intent is predicted using the personalized multimodal RBM.