189 results about "Degree of interest" patented technology

The invention discloses a method for recommending personalized information, which is suitable for the wireless Internet. The method comprises the following steps of: recording user behaviors of accessing the wireless Internet and transmitting to a server by using a behavior recording module on a mobile phone; analyzing the contents of pages accessed by a user to obtain a page set interesting to the user; analyzing the user behaviors of accessing the pages to obtain the interestingness of the user for the pages; combining the interested page set and the interestingness of the pages to establish a user interest model; and carrying out dimensional simplification to a user term matrix and calculating the similarity of term sets to generate recommended personalized information. By adopting the technical scheme, the method can automatically record and analyze the user behavior and excavate user attributes and preferences to realize the matching of the user attributes and information contents and actively recommend the information to the user.

A method and apparatus for selecting additional content to display to a user when the user requests base content is provided. A user profile of the user having user interest scores of categories or keywords is received, each user interest score reflecting the degree of interest the user has in the category or keyword. Performance scores reflecting the probability that a user having particular user interest scores will select additional content associated with particular categories or keywords is also received. In addition, revenue amounts associated with each category or keyword of the user profile is received. The user interest scores, performance scores, and revenue amounts are used to produce an expected revenue amount for each category or keyword in the user profile. Additional content to be sent to the user is then selected using the determined expected revenue amounts.

Method and system to enable a user to view large collections of hierarchically linked information on a computer based display. A tree structure visualization is created which presents a representation of the complete collection of information on the display. The visualization fits completely within a fixed area of the computer based display, negating the need to scroll information into the display area. The visualization is based on identified focus nodes and through calculation of a Degree of Interest (DOI) for each of the nodes based in the structure. Layout and presentation of the visualization structure is based on the DOI values in combination with considerations of available display space. A user may dynamically manipulate views of the structure by selecting one or more focus nodes, thus causing a recalculation of the degree of interest.

A system and method are disclosed for providing metric recommendations by a cloud event log analytics system. The log analytics system includes a user interface which allows users to view metric recommendations, view, modify, annotate, delete, or create log metrics. In a first embodiment, centroid vectors are created from metadata associated with user access of log metrics. The centroid vectors are compared to metrics vectors created from log metrics and the results are ranked and provided to users as metric recommendations. In a second embodiment, classification rules are inferred for metric matrix tables containing metadata about log metric usage. Classification rules are assigned to a decision tree used to calculate composite probabilities of interest of log metrics. A recommendation matrix incorporate the composite probabilities of interest to predict the degree of interest an analytics user may have in a log metric for a given role.

Provided is a user interface device (10) that estimates a user's degree of interest, for performing an input process on the basis of the user's degree of interest in a plurality of objects displayed on a screen (26). The device includes a gaze direction detection unit (11) that detects a gaze direction of the user; a gaze duration calculation unit (12) that calculates gaze duration during which the gaze direction has remained on each of the plurality of objects; an eye-attracting force calculation unit (13) that calculates eye-attracting force of each of the plurality of objects; and a degree of interest estimation unit (14) that estimates the user's degree of interest in each of the plurality of objects, such that the longer the gaze duration is the higher the degree of interest becomes, and that the smaller the eye-attracting force is the higher the degree of interest becomes.

The invention discloses a user interest modeling method based on user browsing behavior, comprising the steps of constructing a user interest model in an apparent mode and updating the user interest model in a concealed mode. The step of constructing the user interest model in the apparent mode is a process of primarily establishing and initializing the user interest model through user registration, and the step of updating the user interest model in the concealed mode is realized by analyzing and researching the user access preference according to the condition that users accesses Web pages under the condition of no need of user participation. By using the method, new interests of users can be automatically discovered, and feature items with low interestingness in the user interest model can be eliminated. Therefore, one the one hand, the interest change of users can be better monitored, and on the other hand, the unlimited increase of the user interest model can be controlled in time, and the stability of the interest model is improved.

An interest degree estimating device, which estimates a degree of interest of a user in a video displayed on a screen, includes: an eye gaze detecting unit for detecting an eye gaze direction of the user; a saliency information obtaining unit for obtaining saliency information on a saliency area having salient attractiveness in the video; and a user response analyzing unit for calculating a correlation between the saliency area specified from the obtained saliency information and the detected eye gaze direction, and estimate the degree of interest of the user in the video, the degree of interest being higher as the calculated correlation is higher.

Described are a system and method for notifying electronic meeting participants of information of interest. For an electronic meeting, a relationship is determined between a first participant and one or more second participants having a relationship with the first participant. A degree of interest by the second participants of a portion of the electronic meeting is determined. A notification is generated for the first participant in response to the determined degree of interest.

A communication robot including: a situation change detection unit for detecting writing of information into a situation database; a rule detection unit for detecting, from a rule database, a rule corresponding to the situation indicated by the data stored in the situation database when the writing of information into the situation database is detected by the situation change detection unit; an action inducing parameter setting unit for setting the degree of interest of the detected rule to at least one of movable parts and an audio output unit independently in the situation database; a parameter changing unit for independently changing the degree of interest set for the at least one of the movable parts and the audio output unit; and a command unit for requesting the at least one of the movable parts and the audio output unit to execute the execution command indicated by the detected rule.

The invention discloses a video recommendation method and system. The method comprises the steps that an initial score of a user on a video is calculated according to the length of time of the video and the length of time spent by the user in watching the video; the initial score is standardized in a minimum-maximum standardization mode to obtain a standardization score of the user on the video; according to the difference value between a current moment and the moment when the user watches the video last time, calculating a final score of the user on the video. According to the video recommendation method and system, the influences of the playing time of the video, the user watching frequency and time interval factors on user interestingness are comprehensively considered, and the final recommendation quality is improved.

The invention relates to a commodity recommendation method and device based on an electronic business platform and a server. The commodity recommendation method and device based on the electronic business platform and the server are used for improving the accuracy of individual commodity recommendation. The method comprises the steps that adhesive user groups are screened; user interestingness is acquired; a neighbor set closest to a target user is generated; a commodity recommendation list is generated. According to the technical scheme, the obtained adhesive user groups can be more accurate and efficient; due to the fact that only the interestingness of each user in the adhesive user groups is recorded in an obtained scoring matrix, an evaluation matrix can be filled, and the density of the scoring matrix is improved; the closest neighbor set between the target user and the other users in the adhesive user groups is calculated through the scoring matrix, the similar neighbors of the target user can be searched for more accurately, and then the accuracy of recommending commodities to the target user is improved.

The invention discloses a method for personalized meta-search, which comprises the following steps: establishing an interest database in advance; extracting a use log from the interest database according to a determined keyword to be searched and preprocessing search results returned by a search engine; using the use log to calculate the preprocessed search results and the interest of uniform resource locators (URL) corresponding to the searched keyword in the interest database, and ordering and displaying according to calculation results; and updating the interest database. The invention additionally discloses an application terminal for personalized meta-search. By adopting the method and the application terminal, users can obtain more pertinent and satisfactory search results and the user experience is improved.

The invention discloses a personalized recommendation method based on group user behavior analysis, which belongs to the technical field of computer network application and provides a personalized recommendation method based on group user interest change, wherein a recommendation list with higher accuracy is obtained rapidly and effectively by collecting temporary dynamic interest degree of a large number of users to a commodity; in addition, the effect of time factor to a user's interest degree is analyzed quantitatively; by combining the time from contacting goods to buy goods by public users and the distribution diagram of the number of users who buy the goods at different time sections, so the accuracy of recommendation is improved; and after fully analyzing the datum of users' behaviors and summarizing the interest of users, the interest correlation between the goods and users is calculated.

The present invention provided a method for updating user profile, and the user profile includes like-degree of the user for at least one content feature. The method includes the following steps of: (a).monitoring the user's behavior to a playing program; (b).acquiring a interest degree of the user for the program according to the behavior to the predetermined content features of the program; (c).adjusting contains like degree and weight of a the interest degree correspondingly according to the like degree for the corresponding content feature in the user profile; (d).modifying the like degree in the user profile for the corresponding content feature according to the adjusted interest degree to the predetermined content features of the program.

The present invention provides an information displaying apparatus which efficiently arouses an interest of the audience member to content to be displayed.An information displaying apparatus (10) includes: a displaying unit (14) which displays first content on a display; an audience state detecting unit (11) which detects an audience state representing a physical state of an audience member positioned in front of the display; an interest degree estimating unit (12) which estimates an interest degree based on the audience state detected by the audience state detecting unit (11), the interest degree indicating a degree of interest of the audience member in the first content displayed on the display by the displaying unit (14); and a display control unit (13) which causes the displaying unit (14) to display second content with a clarity degree or an exposure degree of at least a part of the second content reduced below a predetermined clarity degree or a predetermined exposure degree when magnitude of a change rate of the interest degree estimated by the interest degree estimating unit (12) is smaller than a first threshold.

The invention provides a method and a system for intelligent push of an individualized advertisement of a retail store. The method comprises the steps of acquiring a face image of a customer in a viewregion of an advertisement putting device; carrying out characteristic extraction on the face image to obtain characteristic information of a gender and an age of the face of the customer in the viewregion; and pushing a product advertisement with a highest comprehensive attention index corresponding to the characteristic information of the face of the customer by the advertisement putting device. The comprehensive attention index is formed by fusing a product transaction index, a product category attention index and a product advertisement attention index; each index is obtained by collecting images with cameras at multiple places and dynamically analyzing the images with a computer; and the indexes are updated at set intervals. According to the method and the system for intelligent push of the individualized advertisement of the retail store, a customer group is divided according to age and gender; the product advertisement with the highest attention is put according to the type ofcustomers; a putting strategy summarizes various types of information such as long-term purchase behaviors of customers, the interestingness to the product and the advertisement and the like; the advertisement putting effect is effectively improved, and the comprehensive attention index of the product can be updated according to the behaviors of the customers.

The invention discloses a live broadcast room recommending method and system based on weighted k nearest neighbor scores and relates to the field of popularization of live broadcast rooms. The method comprises the steps of obtaining a live broadcast room watching vector of each user in a live broadcast platform; calculating a similarity between every two users according to the live broadcast room watching vectors; selecting the appointed number of neighbor users for each user according a similarity descending sort method; calculating degree of interest of each user for each watched live broadcast room according to the similarities and the neighbor users of each user; and selecting the appointed number of recommended live broadcast rooms for each user according to a degree of interest descending sort method. According to the method and the system, the recommended live broadcast rooms are evaluated and selected according to the degree of interest calculated according to the similarities; the recommended live broadcast rooms are more consistent with the hobbies, interests and individual demands of the users; the recommending accuracy is relatively high; and the recommending effect is relatively good.

A server delivering the degree of interest in broadcast programs and a method thereof and a computer program of the method are provided. The server utilizes information, which is being transmitted and has topics on the Internet, and delivers the information to users who use the information when the users select a broadcast program. Further, the server delivers a message list including reference information for programs to the users. With this, the users can easily collect the reaction of other users for programs. The server provides a message storing means for storing messages supplied from viewers, a message counting means for counting the number of messages for each program and stores the counted number of message for each program in a database of the degree of interest in broadcast programs. And the server delivers the number of message for each program, as the degree of interest in each program, to the users by obtaining from the database of the degree of interest in broadcast programs.

The invention specifically relates to an individualized learning-oriented educational resource recommendation method and system. The method comprises the following steps of: S1, acquiring basic characteristic data of learners and establishing a resource interestingness model and a learning style model of the learners according to the basic characteristic data, wherein the basic characteristic data comprises identity information, learning behavior records and educational resource operation records of the learners; S2, establishing a learner characteristic model according to the resource interestingness model and the learning style model; S3, calculating the similarity between different learners or the similarity between different educational resources according to the learner characteristic model; and S4, generating a target learner-oriented educational resource recommendation result according to the similarity between different learners or the similarity between different educational resources. Through the technical scheme provided by the invention, the target learner-oriented education resource individualized recommendation can be realized.

A method and apparatus is disclosed herein for enhancing accuracy of jumping by incorporating interestingness estimates. In one embodiment, the method comprises serially displaying a sequence of page images; receiving a user input to stop sequencing through the page images; determining a location of a page image in the sequence of page images representing a point at which the user intended to stop in the sequence of page images but for display speed of the sequence of images and user reaction time in providing an indication of the point at which the user intended to stop, the location being selected based on visual distinctiveness of the page image at the location and the reaction time associated with the user; and automatically jumping back to the page image at the location in the sequence of page images.

A content managing apparatus includes: an obtaining unit which obtains (i) a first content item held by a first user, (ii) a metadata item that indicates attribute information for classifying the first content item, and (iii) information on a sharing state, between the first user and a second user who is a user other than the first user, of a second content item having a metadata item identical to the metadata item held by the first content item; a degree of interest calculating unit which calculates a degree of interest that is an index indicating an interest of the second user on the metadata item; and a managing unit which manages the first content item based on the degree of interest of the second user.

The invention provides a large-scale mixed heterogeneous storage system-oriented node fault prediction system and method. A time sequence-based association rule mining algorithm is adopted to construct a node fault prediction system architecture, and a main process of node fault prediction includes: collecting state data and log information of each storage node; carrying out data preprocessing, and generating sequence modes on the basis of a sliding window; using the sequence modes and fault sequences, which are extracted in a fault identification process, together as input of an association rule algorithm, and outputting output results as typical fault sequences; carrying out matching on the typical fault sequences and sequence modes generated in real time; and if a matching result meetsan established rule, issuing early warning to notify a system administrator, and giving feedback to a prediction result by the administrator according to a subjective interest degree. According to thesystem and method, real-time online fault prediction is carried out for nodes of a large-scale mixed heterogeneous storage system, and accuracy and recall which are better than those of existing fault prediction algorithms and better scalability can be obtained.

A data fusion based video program recommendation method comprises the following steps: 1) collection of behavioral data of users: collecting the behavioral data of the users in browsing video websites and storing the behavioral data in a database; 2) data fusion: converting the behavioral data of a user in browsing a video program into the interest value of the user in the video program; and 3) program recommendation: according to the interest value of the user in a few programs, recommending the programs in which the user has high interest value to other users having the same favorites, wherein the behavioral data in browsing comprise behavioral data in playing. The duration ratio r is obtained by dividing the duration of the programs played by the users by the total duration of the programs. The higher the duration ratio r is, the higher the interest value is. As long as the users play the programs and other behavioral data of the users related to the interest value are fused, the program lists to be recommended can be generated more accurately and the degree of satisfaction of the users with the recommended programs is greatly improved.

The application discloses a user involving project recommendation method. The method comprises: acquiring a project set to be recommended to target users; acquiring a user set formed by users that have been involved in projects in the project set to be recommended to the target users; acquiring an influence value of each user in the user set ; according to projects involved in participation behaviors of the users, acquiring similarity degree between each user of the user set and the target users; considering the influence value of each user in the user set and the similarity degree between each user of the user set and the target users, calculating predicted values of degree of interest the target users have on each project in the project set to be recommended to the target users; and considering the predicted values, selecting at least one project from the project set to be recommended to the target users, and recommending the selected at least one project to the target users. According to the user involving project recommendation method and apparatus, the recommendation accuracy and the quality of recommended projects are improved, and the recommended projects are higher in representativeness and effectiveness.