40results about How to "In line with interest" patented technology

The embodiment of the application discloses methods, devices and equipment of information recommendation. One of the methods includes: acquiring page data of a first link in a first page and related links or data of the first link when clicking on the first link is detected; and displaying the page data of the first link, and loading the related links or data of the first link in the first page. According to the embodiment of the application, recommendation information (namely the related links or data of the first link) related to the page data of the first link is obtained through currentlyclicking on the first link by a user and is recommended to the user, The information recommendation is enabled to not need to completely rely on currently and commonly used personalized recommendationtechnology, recommended information is the information related to the page data currently viewed by the user, thus the recommended information is enabled to more accord with current interest of the user, probability of clicking on and viewing the recommended information by the user is increased, and then a success rate of information recommendation is increased.

The present invention discloses a website address recommendation method, apparatus and system. The method comprises: acquiring a domain name access historical record of a user, wherein the domain name access historical record comprises a domain name of a website accessed by the user; acquiring a category label corresponding to each domain name in the domain name access historical record; acquiring a target category label according to the domain name access historical record and the category label; acquiring a candidate domain name for recommendation according to the target category label; determining a recommended website address based on the candidate domain name; and presenting the recommended website address in a navigation page browsed by the user. By means of the method, apparatus and system disclosed by the present invention, when the user browses the navigation page, the website address that better coincides with the interest of the user is provided for the user, and therefore personalized website address navigation is provided for different users.

The invention provides an interactive music on-demand method, device and terminal. The method comprises the steps of obtaining on-demand requirement information; judging whether to perform on-demand inquiry or not according to the inquiry requirement condition, and if yes, generating on-demand inquiry voice according to the on-demand requirement information and the corresponding on-demand option set; acquiring on-demand selection information corresponding to the on-demand inquiry voice; and playing music according to the on-demand selection information. The intelligent playing device obtains an on-demand requirement voice sent by a user; the on-demand inquiry voice is fed back, the song searching and recommending range can be gradually narrowed through multi-round voice conversation in thevoice interaction with the user, the real requirement of the user is deeply discovered, the user is guided to materialize the generic requirement, and the finally recommended music better conforms tothe interest of the user.

The invention discloses a method and device for constructing and using a knowledge model of a conversation system, wherein a method for constructing a knowledge model of a conversation system includes: abstracting at least one subject associated with the knowledge point from the knowledge point in the conversation system; The at least one topic constructs a system topic tree; based on the system topic tree, an association relationship between knowledge points is determined; a conversational system knowledge model is constructed at least based on the system topic tree and the association relationship between each knowledge point. The method of this embodiment abstracts the knowledge points into at least one topic, then uses the topic to construct a topic tree, and then determines the association relationship between the knowledge points according to the topic tree, and then a conversational system knowledge model can be constructed for subsequent heuristics. During the session, questions or answers are recommended to the user, so that questions or content that are more in line with the user's interests can be recommended to the user.

The invention provides a recommendation system scoring prediction and recommendation method based on user behavior tendency probability for scoring and calculating the relationship between an item, a label of the item and the user's tendency scoring of a current recommendation system, and providing a similar item recommendation service for a target user when the target user searches for items in the current recommendation system. The method is characterized by comprising the following steps: 1, building an item database; 2, building a user rating library; 3, calculating the tendency probability prediction scoring P(ur, Tq) of a user ur towards a label Tq; 4, calculating the tendency scoring P(ur, Ii) of the user ur towards an item Ii; 5, calculating the similarity S(Ii, Ij) of the item Ii and an item Ij when a target user u* searches for the item Ij from a current recommendation system; 6, calculating a prediction scoring value r(ur, Ii) of the target user u* towards the item Ii; 7, sorting neighbor items according to the prediction scoring value r(ur, Ii), and recommending the neighbor items ranked in predetermined numbers to the target user u*.

The embodiment of the present application discloses a method, device and equipment for information recommendation. The method includes: when it is detected that the first link in the first page is clicked, acquiring the page data of the first link and the first Related links or data of the link: displaying the page data of the first link, and loading the related link or data of the first link on the first page. According to the embodiment of the present application, the user currently clicks on the first link to obtain the recommended information related to the page data of the first link (ie, the relevant link or data of the first link) and recommend it to the user, so that the information recommendation does not need to completely rely on the currently commonly used Personalized recommendation technology, and the recommended information is information related to the page data currently viewed by the user, so that the recommended information is more in line with the user's current interests, and the probability of the recommended information being clicked by the user is increased, thereby improving the information quality. Recommended success rate.

The invention discloses an interest resource recommendation method based on multi-dimensional attribute attention. A resource recommendation terminal which is in communication connection with a network system with resources is arranged; the resource recommendation terminal is provided with a visual device, a statistic module, a user type dividing module, an attribute attention guide module, a resource grading module, a topN choosing module and an attribute relevancy guide module. By the recommendation method, corresponding attribute attentions can be calculated according to different users, and resources which are most similar to user interests can be recommended. Excellent interest resources can be recommended even though a user does not browse the resources, and when the user browses the resources, similar predicted interest resources which are relevant to the resources are recommended.

The invention provides a video recommending method based on a time factor. The method comprises the steps that a corresponding user-video scoring matrix is constructed by collecting operation scoring information on videos by users and recording every operation time, and the operation behaviors of the users are analyzed through three different time angles such as the time span, the time sequence, the time period and the like, so that an interest model of the users is built, wherein according to the time span, the larger the time span of the last video watching time is, the smaller the interest in the videos of the users is; according to the time sequence, the sequence in which the users watch the videos refers to the internal relation between the videos; according to the time period, when the users watch the videos more than once, the influence is caused every time the videos are watched; finally, a system recommends the videos in which the users interest according to the latest interests of the users. According to the video recommending method, various points of view of time are comprehensively considered, and the constructed interest model can better adapt to the user interest shifting.