Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for generating personalized smart responses. A messaging system receives a message transmitted as part of a communication session between a first user and a second user and determines a set of candidate responses for replying to the message. The messaging system filters the set of candidate responses based on a personalized vocabulary for the first user, yielding a set of personalized candidate responses. The personalized vocabulary for the first user is determined based on member profile data associated with the first user. The messaging system determines, based on a set of personalized candidate selection rules, a subset of the candidate responses, yielding a set of recommended responses to the message, and causes the set of recommended responses to be presented on the second client device.

Abstract: In an example embodiment, knowledge discovery using deep learning is combined with the scalability and personalization capabilities of generalized additive mixed effect (GAME) modeling. Specifically, features learned in a last fully connected layer of a deep learning model may be used to augment features used in a fixed or random effects training portion of a GAME model.

Abstract: Techniques for predicting sequential data using generative adversarial networks are disclosed herein. In some embodiments, a method comprises: receiving a request associated with a user of an online service; in response to the receiving of the request, retrieving a first plurality of sequential data points of the user from a profile of the user stored on a database of the online service, the first plurality of sequential data points comprising at least one attribute for each one of a plurality of sequential career points of the user; generating at least one predicted data point for the user based on the first plurality of sequential data points using a generative model, the generated at least one predicted data point comprising at least one attribute for a predicted career point for the user; and performing a function of the online service using the generated at least one predicted data point.

Abstract: Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as Web mining, search marketing, bioinformatics, citation analysis, and epidemiology. A probabilistic model is presented for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. The model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. Under this model, parametric hard and soft relational clustering algorithms are provided under a large number of exponential family distributions.

Abstract: A dome-shaped push switch includes a sheet and a conducting layer disposed at a low surface of the sheet. The sheet has a pressing portion arching upward. The conducting layer is disposed at a lower surface of the sheet. The conductivity of the sheet is greater than that of the sheet. The pressing portion includes at least one through hole penetrating through the pressing portion. The through hole has a side wall, the side wall sequentially has a shear surface and a tear surface from bottom up, and a fillet is provided between the shear surface and a lower surface of the pressing portion.

Abstract: A dome-shaped push switch includes a sheet and a conducting layer disposed at a low surface of the sheet. The sheet has a pressing portion arching upward. The conducting layer is disposed at a lower surface of the sheet. The conductivity of the sheet is greater than that of the sheet. The pressing portion includes at least one through hole penetrating through the pressing portion. The through hole has a side wall, the side wall sequentially has a shear surface and a tear surface from bottom up, and a fillet is provided between the shear surface and a lower surface of the pressing portion.

Abstract: This invention discloses an elliptical exercise apparatus that is characterized in having left and right tracks disposed in a guider frame which is pivotally coupled to a rear portion of the elliptical exercise apparatus. When a user uses the elliptical exercise apparatus, the guider frame is at a use position. When the user folds the elliptical exercise apparatus, the guider frame is at a storage position. A user can complete folding procedure merely by operating the guider frame without lifting some heavy components of the elliptical exercise apparatus.

Abstract: This invention discloses an elliptical exercise apparatus that is characterized in having left and right tracks disposed in a guider frame which is pivotally coupled to a rear portion of the elliptical exercise apparatus. When a user uses the elliptical exercise apparatus, the guider frame is at a use position. When the user folds the elliptical exercise apparatus, the guider frame is at a storage position. A user can complete folding procedure merely by operating the guider frame without lifting some heavy components of the elliptical exercise apparatus.

Abstract: One particular embodiment clusters a plurality of documents using one or more clustering algorithms to obtain one or more first sets of clusters, wherein: each first set of clusters results from clustering the documents using one of the clustering algorithms; and with respect to each first set of clusters, each of the documents belongs to one of the clusters from the first set of clusters; accesses a search query; identifies a search result in response to the search query, wherein the search result comprises two or more of the documents; and clusters the search result to obtain a second set of clusters, wherein each document of the search result belongs to one of the clusters from the second set of clusters.

Abstract: Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as Web mining, search marketing, bioinformatics, citation analysis, and epidemiology. A probabilistic model is presented for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. The model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. Under this model, parametric hard and soft relational clustering algorithms are provided under a large number of exponential family distributions.

Abstract: This invention discloses an elliptical exercise apparatus that is characterized in having left and right tracks disposed in a guider frame which is pivotally coupled to a rear portion of the elliptical exercise apparatus. When a user uses the elliptical exercise apparatus, the guider frame is at a use position. When the user folds the elliptical exercise apparatus, the guider frame is at a storage position. A user can complete folding procedure merely by operating the guider frame without lifting some heavy components of the elliptical exercise apparatus.

Abstract: One particular embodiment clusters a plurality of documents using one or more clustering algorithms to obtain one or more first sets of clusters, wherein: each first set of clusters results from clustering the documents using one of the clustering algorithms; and with respect to each first set of clusters, each of the documents belongs to one of the clusters from the first set of clusters; accesses a search query; identifies a search result in response to the search query, wherein the search result comprises two or more of the documents; and clusters the search result to obtain a second set of clusters, wherein each document of the search result belongs to one of the clusters from the second set of clusters.

Abstract: A ball joint includes a ball member, a socket member, and a resilient pressing mechanism. The ball member couples with the socket member. The resilient pressing mechanism is positioned between the ball member and the socket member, applying compression to cause the ball member to tightly contact the socket member. The resilient pressing mechanism includes a plurality of springs positioned in parallel between the ball member and the socket member.

Abstract: Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as Web mining, search marketing, bioinformatics, citation analysis, and epidemiology. A probabilistic model is presented for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. The model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. Under this model, parametric hard and soft relational clustering algorithms are provided under a large number of exponential family distributions.

Abstract: A method for identifying facial features comprises following steps: An image tracing step is performed to receive video data of a plurality of face images and to obtain a real-time background image from the video data by a video tracing technique. A data calculating step is performed to calculate a video data difference between a current face image and the real-time background image. A process setting step is performed to set an iteration number according to the video data difference. A coordinate requesting step is performed to obtain facial feature coordinates of a previous face image, the previous one of the current face image, serving as initial facial feature coordinates. A localization step is performed to obtain current facial feature coordinates of the current image by conducting an iterative calculation according to the iteration number and based on the initial facial feature coordinates.

Abstract: Techniques for predicting a user response to content are described. According to various embodiments, a configuration file is accessed, where the configuration file includes a user-specification of raw data accessible via external data sources and raw data encoding rules. In some embodiments, the raw data includes raw member data associated with a particular member and raw content data associated with a particular content item. Thereafter, source modules encode the raw data from the external data sources into feature vectors, based on the raw data encoding rules. An assembler module assembles one or more of the feature vectors into an assembled feature vector, based on user-specified assembly rules included in the configuration file. A prediction module performs a prediction modeling process based on the assembled feature vector and a prediction model, to predict a likelihood of the particular member performing a particular user action on the particular content item.

Abstract: A robot arm assembly includes a first robot arm, a second robot arm, a third robot arm, a connecting base, a first driving assembly, a second driving assembly, a third driving assembly, and a cable receiving tube. The connecting base includes a housing and a protection cover. A sidewall of the housing defines an opening. The protection cover covers the opening and is mounted on the housing. An end of the housing defines a cable inlet. The first driving assembly rotates the first robot arm. The second driving assembly rotates the second robot arm. The third driving assembly rotates the third robot arm. The cable receiving tube is received in the first robot arm, the second robot arm, and the third robot arm.

Abstract: Method, apparatus, and programs for customizing a web site are provided. In one example, a method for customizing a web site is provided. One or more representations corresponding to one or more customizable components of a web site are provided. The one or more representations are to be displayed on a display screen to a user. An input entered by the user and directed to a specific customizable component of the web site is received. How to customize the specific customizable component of the web site is determined based on the input. An instruction is generated with respect to the customizable component. The instruction is used to implement customization of the specific customizable component of the web site in accordance with the input from the user.