4 results about "Preference weight" patented technology

The invention provides a commodity recommendation method and system based on consumer behaviors, and the method comprises the steps: firstly extracting explicit behavior features and implicit preference features of consumers in different context scenes, and determining node preference indexes of consumption behaviors in different context scenes; generating a short-term intention chain and a long-term preference chain of the consumer according to the node preference index, and further constructing an element feature map reflecting consumer consumption behavior preference according to a mapping association relationship between the short-term intention chain and the long-term preference chain; extracting the preference weight of each preference node in the element characteristic spectrum under different context scenes; and detecting the matching degree between the element characteristic spectrum and the current consumption behavior characteristics, and when the matching degree is lower than a preset threshold value, performing preference updating on the element characteristic spectrum based on the preference weight corresponding to each preference node and the current consumption behavior characteristics, thereby generating a commodity recommendation list. By adopting the scheme of the invention, personalized commodity recommendation based on different context scenes can be realized in an internet e-commerce platform.

The embodiment of the invention provides a travel information processing method and device, a storage medium and a program product. In the scheme, based on semantic scene intelligent perception and preference weight dynamic allocation, the de-duplication intensity gear of each dimension can be adaptively determined, the macroscopic performance target is accurately conducted to the preference dimension hierarchy, and a hierarchical and parameterized control link is formed. And secondly, through the synergistic effect of a degradation mechanism and an upgrade mechanism, when candidate results are insufficient, intelligent circle expansion and amount compensation are performed from low to high according to preference weights, and when the results are excessive, dimension-by-dimension tightening is performed according to the preference weights, so that the number of the results is rapidly adjusted to the optimal interval while the core preference is not weakened. More importantly, according to the scheme, a traditional duplicate removal mode with a fixed threshold value is abandoned, so that a duplicate removal strategy can be continuously evolved according to a real-time scene and user preference, finally, on the premise of guaranteeing the accuracy of journey recommendation, the diversity and individuation degree of recommendation results are remarkably improved, and accurate and rich specialized journey selection is provided for the user.

Method for multi-objective optimization of a list of time slots for stakeholders (A, B, …), (a) wherein an initial list (L0) of flights in time slots is provided, (b) wherein each stakeholder (A, B, …) provides preferences in the format of a weight map (wi) comprising at least a time preference value (ti) assigned to each combination of time slot and item-ID for the respective stakeholder, (c) wherein a value of satisfaction (v) is defined that corresponds to the fulfilment of the preferences by distributing either the time slots or item-IDs in a specific list (Li), and wherein a first objective is provided that consists of generating an improved list (Lf) in which the value of satisfaction (v) is the highest, (d) wherein repeatedly for a predefined number of times two items are permutatively swapped and multiple times repeat: (e) generate a next generation of candidate lists comprising a predefined number of lists (Lc2i) by (e.1) taking a predefined number of candidate lists with best specific values of satisfaction (vi) of the given generation and for each of the chosen lists doing a predefined number of swaps according to a constraint (cm), and / or (e.2) taking a predefined number of candidate lists and combine two or more of the chosen lists according to a constraint (cc), each list having a specific value of satisfaction (vi).

This invention relates to the field of big data analytics, and discloses a method and system for analyzing consumer behavior in cultural tourism marketing. The invention quantifies the impact of context by introducing context intensity and duration, and dynamically adjusts user preference weights accordingly. This allows the system to more sensitively capture and respond to the user's real needs in the current context, avoiding erroneous recommendations caused by over-reliance on long-term preferences. Furthermore, the progressive weight recovery mechanism effectively avoids the problem of over-correction that may occur after the context ends, ensuring the consistency and stability of recommendations. Therefore, this invention effectively solves the problem in existing cultural tourism marketing systems where the recommendation decision-making mechanism becomes rigid and unable to accurately respond to the user's immediate needs when the user's travel context changes temporarily; it significantly improves the accuracy of cultural tourism marketing recommendations and user satisfaction, optimizes user experience, and improves the utilization efficiency of marketing resources.