19 results about "Search engine optimization" patented technology

The present disclosure provides a search engine optimization (SEO) system comprising a remote server. The remote server comprises a memory with a set of executable routines and a search engine database with multiple fields of applications, each associated with multiple URLs indexed with a user engagement matrix, written data, and a search engine ranking. A processor acquires a web link from a computing device, extracts textual content, analyzes relevancy, and retrieves relevant URLs. The processor evaluates a thematic score, a readability score, and an emotional tone data using NLP techniques, analyzes written data of each URL to determine a topic weight, a legibility weight, and a sentiment tone data, develops a machine learning model, applies the model to recommend content alterations, and renders the alterations at the computing device.

The invention discloses a live broadcast content automatic abstract and structured SEO mark generation method and system, and mainly relates to the technical field of artificial intelligence and search engine optimization. Comprising the following steps: collecting multi-modal data of a live stream in real time, the multi-modal data comprising video data, audio data, interactive text data and metadata; based on the collected multi-modal data, performing multi-modal semantic fusion to generate a semantic event flow with a timestamp; generating a structured SEO mark based on the generated semantic event stream; a request from a search engine crawler is identified and a static response page is generated based on the generated structured SEO tag. The method has the beneficial effects that multi-modal real-time understanding and semantic alignment of live broadcast contents are realized, a dynamic structured SEO mark can be automatically generated, and the collection rate of a search engine, the rich media display effect and user click conversion are remarkably improved.

Embodiments of a method for automatic search engine optimization (SEO) of funnel websites in a tiered software framework comprises: generating at a first tier, a prompt for an artificial intelligence (AI) model to provide recommendations for improving search rankings of a seed website; receiving from the AI model, SEO format recommendations, and SEO content recommendations; generating websites by modifying the seed website according to a unique selection from the SEO format recommendations and the SEO content recommendations; associating each website with a corresponding SEO score based on performance in a web search; ranking and sorting the websites according to the respective SEO scores; generating choices of the ranked websites; providing the choices to a second tier and receiving a selection therefrom for a number of iterations; and deploying, by the funnel website application the final selection at a public universal resource locator.

An object of a system according to an embodiment is to provide a consumer with optimal purchase timing and discount information, and to allow a store establishment company to secure a budget necessary for SEO countermeasures.SOLUTION: A system includes a collection part, a provision part, an operation part, means, and a budget part. The collection unit collects a purchase history and a browsing history of a consumer. The providing unit provides appropriate purchase timing or discount information based on the data collected by the collecting unit. The operating unit operates points that are not used. The means increases the exposure opportunity of its own company merchandise by the increase of profits due to the increase of the number of consumers and point operation. The budget section secures a budget for devoting a budget required for the SEO countermeasure.SELECTED DRAWING: Figure 1

The invention discloses a diffusion enhancement relation-based triple extraction method, which comprises the following steps of: 1) inputting a Chinese text into a BERT model, and converting the Chinese text into a corresponding index to obtain word embedding information; 2) inputting word embedding information into a triple diffusion model, and performing noise addition, feature fusion and de-noising processing to obtain a predicted triple; 3) inputting word embedding information into the character feature extraction network model, learning semantic information through a multi-layer perceptron and a double-affine attention mechanism in combination with relative position coding and a multi-head attention module, relieving a label imbalance problem by adopting a word embedding disturbance mechanism, and outputting a relation triple matrix; and 4) respectively decoding the triads obtained in the two steps, and taking union sets to obtain a final relation triad. According to the method, the boundary diffusion information and the character-level semantic information are fused, so that the problems that Chinese semantics are complex, natural separators are lacked, small-field data semantics extraction is insufficient, extraction of a traditional decoding method is incomplete, labels are unbalanced and the like are effectively solved, the accuracy and integrity of Chinese relation triple extraction and model stability are remarkably improved, and the method is suitable for large-scale popularization and application. The method is suitable for various natural language processing application scenes such as information questions and answers and search engine optimization.

An object of the system according to the embodiment is to quickly generate a high-quality landing page or blog article based on a description or specification of a product and apply an SEO countermeasure.SOLUTION: A system includes an input unit, a generation unit, and an optimization unit. The input unit receives a description and specifications of a product from a user. The generation part generates a landing page and a related blog article on the basis of the description and specifications of the article received by the input part. The optimization unit applies an SEO countermeasure to the landing page and the related blog article generated by the generation unit.SELECTED DRAWING: Figure 1

A method is provided for generating product description information for a product. The method includes receiving a request to generate the product description information, retrieving product data for the product, and determining user instructions indicated in the request. The method further includes retrieving one or more contextual datasets curated with information relevant to the product. The one or more contextual datasets include one or more of: search engine optimization data, brand standards data, industry or organization norms data, and target consumer preferences data. The method further includes generating the product description information by providing the product data, the one or more user instructions, and the one or more contextual datasets as inputs to a data model to cause the data model to output the product description information. The method further includes providing the product description information for display on a user interface of a device or application.

Embodiments of a method for automatic search engine optimization (SEO) of funnel websites in a tiered software framework comprises: generating at a first tier, a prompt for an artificial intelligence (AI) model to provide recommendations for improving search rankings of a seed website; receiving from the AI model, SEO format recommendations, and SEO content recommendations; generating websites by modifying the seed website according to a unique selection from the SEO format recommendations and the SEO content recommendations; associating each website with a corresponding SEO score based on performance in a web search; ranking and sorting the websites according to the respective SEO scores; generating choices of the ranked websites; providing the choices to a second tier and receiving a selection therefrom for a number of iterations; and deploying, by the funnel website application the final selection at a public universal resource locator.

A website building system includes at least one processor, at least one database, a WBS editor, an SEO tool, an analyzer, a design recommender, a component receiver, a component SEO ranker, and an updater. The database holds SEO performance data for website components. The WBS editor lets a user pick a first website component, shows information, and takes user commands. The SEO tool helps with SEO. Its analyzer, responding to the first component's selection, checks the database for SEO ranking data for that component and others. The design recommender guides design. Its component receiver gets the user-chosen first component. Its component SEO ranker compares the first component's ranking with others to find a higher-ranking second component, then suggests replacement. The updater, on user command, swaps the components on a webpage, preserving and transferring content.

A website building system (WBS) includes at least one processor, one database storing the WBS components and component compositions of multiple websites and multiple per search engine SEO (search engine optimization) behaviors. The per search engine SEO behavior is associated with one website and one search engines and the per search engine SEO behavior contains information that enables ranking the website, the ranking is associated with one of the search engines and an SEO tool running on the processor to provide per search engine recommendations related to changes to the WBS components and component compositions when accessed by at least one search engine based on the per search engine SEO behavior.

Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. The system and methods provide an improvement over existing systems, which do nothing to identify or select valuable view item pages for use in driving traffic from display sites. The system and methods described herein improve the earlier system by predicting the probability of future traffic for a given product based on a number of product level factors as input variables, and identifying a selection of view item pages corresponding to the products with the probability of the highest future traffic in order to maximize the driving natural search traffic to a linked site of the corresponding view item page.

This invention discloses a method and system for automatically summarizing and generating structured SEO tags for live streaming content, primarily relating to the fields of artificial intelligence and search engine optimization (SEO). The method includes the following steps: real-time acquisition of multimodal data from the live stream, including video data, audio data, interactive text data, and metadata; multimodal semantic fusion based on the acquired multimodal data to generate a timestamped semantic event stream; generation of structured SEO tags based on the generated semantic event stream; identification of requests from search engine crawlers; and generation of a static response page based on the generated structured SEO tags. The beneficial effects of this invention are: it achieves real-time multimodal understanding and semantic alignment of live streaming content, and can automatically generate dynamic structured SEO tags, significantly improving search engine indexing rates, rich media display effects, and user click-through rates.

The embodiment of the invention provides a data query method and device based on distributed link tracking, equipment and a medium. The method comprises the following steps: acquiring original link tracking data of each service instance; obtaining a data flow table of a preset data theme, determining a target theme corresponding to the original link tracking data according to the data flow table, and sending the original link tracking data to the target theme; processing the original link tracking data through a stream processing task corresponding to the target theme to obtain target link tracking data corresponding to the original link tracking data; and storing the target link tracking data to a preset search engine, wherein the search engine is used for data query. According to the embodiment of the invention, the storage position of the link tracking data is dynamically determined through the data flow table, and the link tracking data is processed in batches through different flow processing tasks, so that the efficiency and real-time performance of data processing are improved, the processed data is stored in the corresponding search engine, the data storage structure is optimized, and the efficiency of data query is effectively improved.

This invention discloses a keyword search intent analysis method and system based on GEO, relating to the field of search engine optimization technology. The method includes: constructing an initial clustering structure; extracting locally anomalous node regions based on the local sparse distribution characteristics of semantic matching relationships between nodes and keywords in the initial clustering structure; reconstructing semantic paths between nodes based on the asymmetric topological characteristics of the contextual paths between nodes within the locally anomalous node regions, forming an optimized candidate semantic path set; and determining the subdivided search intent corresponding to the target keyword by combining the non-stationary topological characteristics of the state transition topology of the contextual sequences in the candidate semantic path set and using path state inference from a conditional random field model. This invention achieves the parsing of the multi-contextual semantic structure of search keywords, which is beneficial for the subdivided identification of search intent in a generative engine optimization environment.

We provide the system. [Solution] A means for receiving book information from the user's terminal, A means of obtaining basic information from a database based on the received book information, A means of requesting supplementary information from a generative artificial intelligence based on the acquired basic information, A method for generating book information with enhanced SEO effectiveness by integrating supplementary and basic information returned from a generative artificial intelligence, A means of returning the generated book information to the user's device, A system that includes this.

In an embodiment, a set of labeled training data that includes indicators of webpages is received. Each indicated webpage is labeled with one or more categories that were determined for the webpage by a human reviewer. Features, such as text and scripts, are extracted from each indicated webpage, and are used along with the labels to train a classifier to predict one or more categories for a webpage based on the features of the webpage. The trained classifier may be used to associate one or more categories with each domain of a plurality of domains given the categories predicted for some or all of the webpages associated with the domain. A list of domains and associated categories may be used for a variety of purposes including search engine optimization and content filtering.

The current invention relates to a novel system and method for comprehensively assessing and enhancing the quality of Arabic language content on government websites. The system utilizes artificial intelligence (AI), specifically deep learning models, to automatically detect and classify a wide range of errors in Arabic text, including spelling, grammatical, stylistic, and content-related errors. The system further generates statistical data on error frequency and types, facilitating data integrity analysis and identifying potential security risks. Additionally, the system incorporates integrated features for search engine optimization (SEO), performance monitoring, and security testing, thereby providing a holistic solution for improving government websites' overall functionality, usability, and security.

The invention provides an SEO optimization method and system for an MVVM framework, and relates to the technical field of front-end development and search engine optimizing.The method comprises the steps that an SEO optimization framework is started; obtaining a page generation task; the Nginx module receives the page generation task and sends the page generation task to a static page resource generation service module; verifying the page generation task, judging whether the verification is passed or not, and if the verification is passed, pushing the page generation task to a Redis page generation task queue; according to the state of the node, executing a page generation task, and generating an HTML code of the current page; the HTML code is processed, and an HTML file is obtained; uploading the HTML file to a corresponding directory of the OSS; acquiring a user request; and judging whether the user request is crawler access, if so, calculating a corresponding static page file path according to the user request, and otherwise, sending the user request to the original page resource service.

The application discloses a local archive search management system and method based on digital humanities, and particularly relates to the field of archive search management, and comprises an archive information region division module, an archive information collection module, an archive information identification module, an archive information database establishment module, a text information acquisition module, a text information extraction module, an information matching analysis module, an archive search evaluation module, a search engine optimization module and an archive resource security supervision module. The application collects archive information, extracts archive information therefrom, further establishes an archive information database, extracts key word information and search volume from text information input by a user, analyzes to obtain an archive priority matching coefficient, compares the archive priority matching coefficient with a preset archive priority matching coefficient threshold value, automatically searches in the database, and accurately and rapidly outputs archive information searched by the user, so that the digital technology is scientifically and reasonably used and plays a greater role in modern archive management.