33 results about "Preference behavior" patented technology

The invention relates to an automatic tracking method of temperature place preference behaviors in laboratory mice. The method at least includes the steps: a laboratory mice temperature stimulation passage is divided into different temperature zones, each temperature zone is provided with a heating plate and a heating plate temperature sensor, each temperature zone is provided with temperature zone boundary left and right sensor bars, the heating plates are electrically connected with a processing unit through a heating control circuit, the processing unit is respectively connected with the heating plate temperature sensors, the boundary right sensor bars and the boundary left sensor bars through signal wires, the processing unit sets certain temperature spots for the different temperature zones through a human-machine interface, the processing unit controls heating through the heating control circuit, the temperatures of the corresponding temperature zones are controlled in the required temperature field accordingly, the temperature zone boundary of the different temperature zones is used for distinguishing a passing direction of the laboratory mouse through the boundary right sensor bars and the boundary left sensor bars, and the durations of the laboratory mouse being in the temperature zones at different times are provided according to recorded durations, and temperature preference behaviors of the laboratory mice are further understood.

The invention discloses a cross-correlation collaborative filtering method fusing weak trace behavior preferences of a user. According to the method, weak trace behaviors such as clicking and articlebrowsing time are collected, a scoring matrix and a weak trace behavior matrix of the user are constructed, an arithmetic scoring mean value of the user is assigned to represent weak trace behavior preferences of the user, and a scoring enhancement matrix fused with the weak trace behavior preferences of the user is obtained; the correlation between the user behavior preferences and articles can be described more accurately; furthermore, an improved cross correlation coefficient calculation method is provided, a hot penalty coefficient is fused to construct a user-user preference similarity matrix, the preference similarity of the user to the articles is predicted, and recommendation sorting of the articles with similar preferences is optimized. According to the method, the problem of datasparseness in a traditional collaborative filtering method is solved, and the influence of factors such as different user scoring scales and non-preference behaviors caused by popular factors on userpreference similarity calculation is reduced, so that the accuracy of similar preference recommendation results and sorting is effectively improved.

The invention discloses a multi-task TV program recommendation method that integrates user click behavior and user interest preference. In the TV program recommendation, multi-task learning that integrates user click and user interest preference is used to improve the TV program recommendation effect. The method includes: The attention network fusion neural network factorization algorithm establishes the user's click model for TV programs from the user's historical click program data; Finally, the user's click behavior and user's preference behavior are considered comprehensively when recommending, so that the recommended TV programs can better meet the needs of users and improve user satisfaction.

Embodiments of the invention provide an information searching method and apparatus. The method comprises the steps of: carrying out search according to keywords sent by a client, and obtaining a plurality of search results; for each search result, obtaining user preference data corresponding to current search results according to stored historical preference behavior information of a user to the current search results; carrying out sorting on the plurality of search results according to the user preference data corresponding to each search result; and returning a sorting result to the client, so that the client can display the sorting result. According to the scheme, different sorting results can be provided for different users, thereby providing effective information for access decisions of the users to the search results.

The invention discloses a method for recommending fresh agricultural products based on multi-granularity fuzzy data. The method includes: obtaining characteristic parameters of users and products; constructing a characteristic model based on the characteristic parameters to determine user preference parameters; The parameters are input into the multi-granularity fuzzy data recommendation model to obtain the recommendation result, and the recommendation result is fed back to the user. The above solution provided by the present invention is not only based on the similarity between the user's preferred product and the recommended product, but also considers user satisfaction. Therefore, the recommendation can not only recommend products that meet the user's preferred behavior, but also generate the best recommendation for the user on this basis. For the current fresh agricultural products e-commerce platform, this will have great practical significance. It can not only increase the conversion rate and bring higher profits, but also improve user experience and increase user viscosity, so as to promote the promotion of fresh agricultural products in the current market. Stand out in the increasingly competitive market of e-commerce.

The invention provides a testing device and a testing method for testing environmental preference behaviors of fishes. The device is characterized in that water inlet pipes with a flow regulator and water outlet pipes with a flow regulator are respectively installed at the two ends of a water trough, one ends of the water inlet pipes are communicated with a pressure-bearing water tank, flow conditioning meshes are respectively installed at the communicating ports of the water inlet pipes which are communicated with the water channel, upper flow guide baffles are installed between the water inlet pipes and the water outlet pipes to form flow guide channels, isolating nets are installed at the front ends of the water inlet pipes and the water outlet pipes, and the pressure-bearing water tank is connected with a variable-frequency water pump and a variable-frequency regulator. The method comprises the steps of 1) preparation before testing; 2) testing and correction of the testing device; 3) testing of preference behaviors of fishes; 4) testing data acquisition and preference index calculation; 5) maintenance and cleaning of the device. The testing device and the testing method for testing the environmental preference behaviors of the fishes can realize researches on the preference behaviors under various environmental factors such as flowing speed, river bed materials and illumination according to different environmental factors which are distributed in an experimental area.