4 results about "Web page ranking" patented technology

The present application relates to a method, apparatus, device, and medium for detecting bad web pages based on multimodality. The method includes: obtaining a web page to be detected, determining text feature information consisting of the web page title, web page text, web page tag, and web page address, image feature information consisting of a web page screenshot, and position feature information consisting of the one-dimensional position and two-dimensional coordinates of the text image, fusing the three features to form a comprehensive vector of the text and image position, entering the multimodal self-attention network, and converting the vector into a two-dimensional vector through hidden layer linear mapping and nonlinear activation for normalization. When the probability of a bad web page in the two-dimensional vector is greater than the probability of a normal web page, the web page to be detected is determined to be a bad web page. The present application can more accurately identify bad content, prevent website designers from taking improper means to improve web page rankings, promote the purification of the Internet environment, and ensure users' network security.

Systems and methods for generating single-node representations in graphs composed of linked nodes. The present technology enables dynamic generation of individual node embeddings in sub-linear time (less than O(n), where n is the number of nodes in the graph G), using only the PPR vectors of the individual nodes and a random projection to reduce the dimensionality of the PPR vectors of that node. In one example, the present technology includes a computer-implemented method comprising: obtaining, from a database, a graph having a plurality of nodes; generating, for a given node of the plurality of nodes, a personal PageRank vector; and producing, for the given node, an embedding vector by randomly projecting the personal PageRank vector, wherein the embedding vector has a lower dimensionality than the personal PageRank vector.

The present invention relates to a method and system for adjusting the ranking of web page search results based on machine learning. The method comprises: constructing a dataset corresponding to a web page; updating the web page dataset based on historical operation information; obtaining the user's current search information; obtaining the semantic similarity between the user's current search information and the web page dataset information, adjusting the web page ranking based on the semantic similarity to obtain a first ranking; adjusting the first ranking based on a user model and a crowd model to obtain a second ranking; and adjusting the second ranking based on the semantic similarity between the user's historical search information and the current search information to obtain a third ranking. The present invention fully considers the user's historical operations on the web page, matches the user's operations with the search information, and updates the web page dataset information based on the search information, fully reflecting the participation of user behavior in search results.

System and method for generating context-aware pageranks according to certain embodiments. For example, a method includes: generating a plurality of vector elements of a pagerank vector for a page based on a plurality of search contexts, each vector element of the plurality of vector elements corresponding to a respective search context, each search context of the plurality of search context corresponding to a respective security level of a plurality of security levels; obtaining one or more bleed factors for the plurality of search contexts, each bleed factor of the one or more bleed factors associated with two search contexts of the plurality of search contexts having two adjacent security levels of the plurality of security levels; and adjusting at least one vector element of the plurality of vector elements based on the one or more bleed factors.