Abstract: Embodiments of the present application relate to a multilingual mixed search method, a system for multilingual mixed searching, and a computer program product for multilingual mixed searching. A multilingual mixed searching method is provided. The method includes receiving a query word entered by a user and identifying source language of the query word, translating the query word from the source language to query words of a plurality of target languages, the plurality of target languages being different than the source language, using the query word in a corresponding target language as a basis for searching an index of web page information corresponding to the corresponding target language and obtaining web page information in the corresponding target language, from the web page information obtained from the index corresponding to the corresponding target language, and translating the obtained web page information from the corresponding target language to the source language.

Abstract: The present disclosure introduces a method and an apparatus for searching images. With respect to each image in an image searching database, respective labels of respective images are generated based on description information corresponding to the respective images. A corresponding relationship between the generated respective labels and the respective images is stored. Based on a received image searching request, description information corresponding to an image for search in the image searching request is obtained. Based on the description information of the image for search, the label of the image for search is generated. Based on the stored corresponding relationship between the respective labels and the respective images, one or more images corresponding to the label of the image for search are determined. The determined one or more images are sent to the client terminal that sends the image searching request.

Abstract: Ordering search results may include obtaining an exposed log file from a log system, computing a Bayesian posterior probability for relevancy between the log file and a search request, computing an expected value of the relevancy between the log file and the search request based on the Bayesian posterior probability, storing the search request and an identifier of the log file as a key and the expected value of the relevancy between the log file and the search request as a value into a search data structure, in response to receiving a search request submitted by a user, finding expected values of relevancy between the submitted search request and log files that are relevant to the submitted search request from the search data structure, and ordering the found log files in a descending order of the expected values.

Abstract: Ordering search results may include obtaining an exposed log file from a log system, computing a Bayesian posterior probability for relevancy between the log file and a search request, computing an expected value of the relevancy between the log file and the search request based on the Bayesian posterior probability, storing the search request and an identifier of the log file as a key and the expected value of the relevancy between the log file and the search request as a value into a search data structure, in response to receiving a search request submitted by a user, finding expected values of relevancy between the submitted search request and log files that are relevant to the submitted search request from the search data structure, and ordering the found log files in a descending order of the expected values.

Abstract: Ordering search results may include obtaining an exposed log file from a log system, computing a Bayesian posterior probability for relevancy between the log file and a search request, computing an expected value of the relevancy between the log file and the search request based on the Bayesian posterior probability, storing the search request and an identifier of the log file as a key and the expected value of the relevancy between the log file and the search request as a value into a search data structure, in response to receiving a search request submitted by a user, finding expected values of relevancy between the submitted search request and log files that are relevant to the submitted search request from the search data structure, and ordering the found log files in a descending order of the expected values.

Abstract: The present disclosure provides an example information classification method and system based on product recognition. When a request for product recognition is received, one or more candidate product words of product profile information for recognition are determined. One or more characteristics of the product profile information are extracted based on the determined candidate product words respectively. Based on the candidate product words and their corresponding characteristics, the learning sub-model and the comprehensive learning model determine a product word corresponding to the product profile information. The product profile information is classified based on the product word. The present techniques implement automatic classification of the product profile information and improve an efficiency of information classification.

Abstract: Embodiments of the present application relate to a multilingual mixed search method, a system for multilingual mixed searching, and a computer program product for multilingual mixed searching. A multilingual mixed searching method is provided. The method includes receiving a query word entered by a user and identifying source language of the query word, translating the query word from the source language to query words of a plurality of target languages, the plurality of target languages being different than the source language, using the query word in a corresponding target language as a basis for searching an index of web page information corresponding to the corresponding target language and obtaining web page information in the corresponding target language, from the web page information obtained from the index corresponding to the corresponding target language, and translating the obtained web page information from the corresponding target language to the source language.

Abstract: The present disclosure provides techniques to solve problems (e.g., the low efficiency and a waste of resources) derived from conventional methods. These techniques may include extracting, by a computing device, the first N keywords appearing the most in target information published by target users as target words, and creating an inverted index based on information on a page of the target users and the target words, wherein the inverted index includes a target field and a page information field, and N is an integer. The computing device may receive an inquiry phrase and determine target users matching the inquiry phrase in the inverted index based on the inquiry phrase. The computing device may calculate a relevance between the matched target users and the inquiry phrase through the target field and the page information field, and return a certain result based on the relevance.

Abstract: Ordering search results may include obtaining an exposed log file from a log system, computing a Bayesian posterior probability for relevancy between the log file and a search request, computing an expected value of the relevancy between the log file and the search request based on the Bayesian posterior probability, storing the search request and an identifier of the log file as a key and the expected value of the relevancy between the log file and the search request as a value into a search data structure, in response to receiving a search request submitted by a user, finding expected values of relevancy between the submitted search request and log files that are relevant to the submitted search request from the search data structure, and ordering the found log files in a descending order of the expected values.

Abstract: Ordering search results may include obtaining an exposed log file from a log system, computing a Bayesian posterior probability for relevancy between the log file and a search request, computing an expected value of the relevancy between the log file and the search request based on the Bayesian posterior probability, storing the search request and an identifier of the log file as a key and the expected value of the relevancy between the log file and the search request as a value into a search data structure, in response to receiving a search request submitted by a user, finding expected values of relevancy between the submitted search request and log files that are relevant to the submitted search request from the search data structure, and ordering the found log files in a descending order of the expected values.

Abstract: Ordering search results may include obtaining an exposed log file from a log system, computing a Bayesian posterior probability for relevancy between the log file and a search request, computing an expected value of the relevancy between the log file and the search request based on the Bayesian posterior probability, storing the search request and an identifier of the log file as a key and the expected value of the relevancy between the log file and the search request as a value into a search data structure, in response to receiving a search request submitted by a user, finding expected values of relevancy between the submitted search request and log files that are relevant to the submitted search request from the search data structure, and ordering the found log files in a descending order of the expected values.