3results about How to "Improve Personalized Experience" patented technology

The application relates to the technical field of data query, in particular to a query result acquisition method and device based on a large model and a medium, the method comprises the following steps: based on a preset large model, acquiring a result keyword sequence corresponding to a target result text output according to a target query statement, converting the result keyword sequence into target bitmap data of a bitmap data structure, and storing the target bitmap data in association with the target query statement in a preset database; when it is judged that the target query statement is received again, obtaining the corresponding result keyword sequence; based on the result keyword sequence, outputting a new result text through the preset large model, and taking the new result text as a current query result corresponding to the target query statement; by storing the logical relationship of the keywords in the query result, the application greatly reduces the occupation of the storage space, improves the query speed when repeatedly querying, and provides great convenience for repeated query of the user.

This application discloses a method for distinguishing left and right positions using a movable rear-seat control screen for vehicles, relating to the field of rear-seat control screen technology. The method includes the following steps: obtaining connection status information between the movable rear-seat control screen and the base of the rear door interior panel control screen; the connection status information includes the conduction status between the positive power port and the ground port, and the conduction status between the positive signal port and the negative signal port; and basing the method on the conduction status between the positive power port and the ground port. This application achieves flexible handheld operation and a stable plug-and-play experience through a mobile phone-like movable control screen combined with a plug-in structure and contact connection design, reducing the barrier to entry and improving human-computer interaction efficiency. Simultaneously, it identifies left and right positions through contact conduction and maintains the determination result, combining a time strategy to achieve functional isolation and dynamic energy consumption management, meeting the needs of multi-user independent control and privacy.

The invention relates to the technical field of electronic commerce, artificial intelligence and information retrieval, and discloses a point shopping mall multi-modal search method based on a vectorization search architecture. According to the core scheme, the method comprises the following steps: receiving multi-mode search input of user texts, images, audios, videos and the like, realizing efficient transmission and fusion processing through RTC and ITC technologies, and generating unified semantic representation; in combination with LLM and ELCTRA algorithms, deep semantic understanding is carried out, and a user query intention vector is generated; the method comprises the following steps: constructing a commodity multi-modal feature vector library (encoding through an ELCTRA / ResNet-50 / WaveNet embedded model group) and a user portrait vector library, and constructing a dynamically updated vector index based on an HNSW algorithm; a candidate commodity set is retrieved by using an ANN algorithm, and personalized sorting is realized through an L2R sorting model (fusing multi-dimensional factors such as user portrait matching degree and commodity correlation); collecting user behavior data, and regularly finely adjusting model parameters and updating indexes through incremental learning. According to the method, the bottleneck of traditional keyword search is broken through, millisecond-level high-concurrency retrieval is realized, the search accuracy and personalized experience are improved, meanwhile, data support is provided for shopping mall operation, the problem of data drift is effectively relieved, and the method is suitable for high-concurrency and multi-mode search scenes of integral shopping malls.