Abstract: A method and apparatus for encoding a geographic location region as well as a method and apparatus for establishing an encoding model, which relate to big data and deep learning technologies in the field of artificial intelligence technologies are disclosed. An implementation includes: determining a to-be-encoded geographic location region; acquiring at least one kind of geographic function information and at least one kind of surface-feature distribution information of the geographic location region; and inputting the acquired geographic function information and the acquired surface-feature distribution information into an encoding model, the encoding model performing embedding on the geographic function information and the surface-feature distribution information, and fusing vector representations obtained by the embedding to obtain an encoding result of the geographic location region.

Abstract: An information search method is provided. The method includes: searching for webpages related to a search request through a search engine; extracting respective texts related to the search request from respective webpages and splicing the texts to obtain a spliced text; obtaining a text segment from the spliced text; and sending the obtained text segment to the search engine, to display the obtained text segment in an information search result through the search engine. The present disclosure can bring great advantages to the search engine in terms of user experience and interaction, and can satisfy user requirements for a function of an intelligent question and answer. Through present disclosure, it is beneficial to directly presenting a short text with higher relevance to the search request to the user, thereby saving time in screening information for the user.

Abstract: The present application discloses a method for building a ranking model, a query auto-completion method and corresponding apparatuses, which relates to the technical field of intelligent search. An implementation includes: acquiring from a POI query log a query prefix input when a user selects a POI from query completion suggestions, POIs in the query completion suggestions corresponding to the query prefix and the POI selected by the user in the query completion suggestions; constructing positive and negative example pairs using the POI selected by the user and the POIs not selected by the user in the query completion suggestions corresponding to the same query prefix; and performing a training operation using the query prefix and the positive and negative example pairs corresponding to the query prefix to obtain the ranking model.

Abstract: The present disclosure provides a method of retrieving a geographic location as well as a method and an apparatus of establishing a similarity model including: acquiring training data from a historical click log, wherein the training data contains a search term, a clicked geographic location associated with the search term as a positive sample, and a non-clicked geographic location as a negative sample; expanding the positive sample and the negative sample based on a co-occurrence relationship between geographic locations by using a historical browsing log; and determining a vector representation of the search term by using the first neural network, and determining a vector representation of the positive sample expanded and a vector representation of the negative sample expanded, by using the second neural network; and training the first neural network and the second neural network so as to maximum a difference between a first similarity and a second similarity.

Abstract: The present application relates to the technical field of communications, and in particular to a method for scheduling spectrum resources and a storage medium. The method for scheduling spectrum resources includes: obtaining a grid according to dividing a cell in a network, each grid corresponding to one resource block or one resource block group; obtaining offline feature data; performing an interference mark on the grid according to the offline feature data, to obtain a mark model; and scheduling spectrum resources according to the mark model.

Abstract: Embodiments of the present disclosure provide a method and a device for evaluating a comment quality, an electronic device, and a computer readable storage medium. The method includes: selecting a metadata key associated with a comment of an object from metadata of the object, the metadata including a plurality of key-value pairs; determining a value corresponding to the metadata key based on the metadata; and evaluating the comment quality based on the comment and the value corresponding to the metadata key.

Abstract: A method and apparatus for determining an outer loop value, a device, and a storage medium are disclosed. The method may include: determining a pre-trained outer loop initialization model based on current feature data of a user equipment (S11); and determining an initialized outer loop value of the user equipment based on a current air interface measurement value of the user equipment and the outer loop initialization model (S12).

Abstract: Embodiments of the present disclosure provide a method and apparatus for presenting information. The method may include: acquiring target release information and a comment information set associated with the target release information; and generating, for comment information in the comment information set, usefulness probabilities and predicted comment scores of the comment information based on the comment information and the target release information. The method may further include: presenting, based on obtained usefulness probability set and predicted comment score set, the comment information in the comment information set.

Abstract: A method for sorting geographic location points, a method for training a sorting model and corresponding apparatuses are disclosed, which relates to the technical field of big data. A specific implementation solution is: receiving a query request for geographic location points of a vertical class from a user; inputting candidate geographic location point data of the vertical class into a preference model of the user, to obtain a preference score of the user for each candidate geographic location point; inputting the preference score of the user for each candidate geographic location point into a sorting model as one of sorting features of each candidate geographic location point, to obtain a sorting score of each candidate geographic location point; and determining, according to the sorting score of each candidate geographic location point, a query result returned to the user.

Abstract: Technical solutions relate to the field of big data technologies. A technical solution includes: pre-training a time series prediction model using first historical regional heat data; and taking second historical regional heat data as a second support set, and further training the time series prediction model using the second support set to adjust model parameters, so as to obtain the regional heat prediction model; and the regional heat prediction model is configured to predict a second query set, and the second query set includes regional heat at a prediction time.

Abstract: Embodiments of the present disclosure provide a method for generating an information assessment model, a method for determining the usefulness of comment information, apparatus, electronic device, and computer-readable medium.

Abstract: A method, an apparatus, a computer device and a readable medium for knowledge hierarchical extraction of a text are disclosed. The method comprises: performing word segmentation on a designated text to obtain a word list, the word list including at least one word arranged in a sequence in the designated text; analyzing part-of-speech of each word in the word list in the designated text, to obtain a part-of-speech list corresponding to the word list; predicting a SPO triple included in the designated text according to the word list, the part-of-speech list and a pre-trained knowledge hierarchical extraction model. By the technical solutions, the SPO triple included in any designated text however loose its organization and structure is may be accurately extracted based on the pre-trained knowledge hierarchical extraction model. Compared to the prior art, the efficiency and accuracy of knowledge hierarchical extraction may be effectively improved.

Abstract: The present application discloses a query auto-completion method and apparatus, a device and a computer storage medium, which relates to the technical field of intelligent search. An implementation includes: acquiring a query prefix input by a user currently, and determining candidate POIs corresponding to the query prefix; acquiring vector representation of query history information of the user and vector representation of each candidate POI; inputting the vector representation of the query history information of the user and the vector representation of each candidate POI into a pre-trained ranking model, so as to obtain a score of each candidate POI; and determining query completion suggestions recommended to the user according to the scores of respective candidate POIs. With the present application, the recommended query completion suggestions may better meet practical requirements of the user.

Abstract: The present disclosure provides a method of retrieving a geographic location as well as a method and an apparatus of establishing a similarity model including: acquiring training data from a historical click log, wherein the training data contains a search term, a clicked geographic location associated with the search term as a positive sample, and a non-clicked geographic location as a negative sample; expanding the positive sample and the negative sample based on a co-occurrence relationship between geographic locations by using a historical browsing log; and determining a vector representation of the search term by using the first neural network, and determining a vector representation of the positive sample expanded and a vector representation of the negative sample expanded, by using the second neural network; and training the first neural network and the second neural network so as to maximum a difference between a first similarity and a second similarity.

Abstract: The present application discloses a query auto-completion method and apparatus, a device and a computer storage medium, which relates to the technical field of intelligent search. An implementation includes: acquiring a query prefix input by a user currently, and determining candidate Points of Interest (POIs) corresponding to the query prefix; acquiring vector representation of spatial-temporal features of each candidate POI; inputting the vector representation of the spatial-temporal features of each candidate POI into a pre-trained ranking model, so as to obtain a score of each candidate POI; and determining query completion suggestions recommended to the user according to the scores of respective candidate POIs; wherein the spatial-temporal features include at least one of a query time feature and a distance feature between each candidate POI and the user. With the present application, a retrieval intention of the user may be better completed, and practical requirements of the user are met.

Abstract: The present application discloses a method for building a ranking model, a query auto-completion method and corresponding apparatuses, which relates to the technical field of intelligent search. An implementation includes: acquiring from a POI query log a query prefix input when a user selects a POI from query completion suggestions, POIs in the query completion suggestions corresponding to the query prefix and the POI selected by the user in the query completion suggestions; constructing positive and negative example pairs using the POI selected by the user and the POIs not selected by the user in the query completion suggestions corresponding to the same query prefix; and performing a training operation using the query prefix and the positive and negative example pairs corresponding to the query prefix to obtain the ranking model.

Abstract: The present disclosure provides a method for extracting a geographic location point spatial relationship, and a method and apparatus for training an extracting model, and relates to the technical field of big data. A specific implementation solution is: obtaining second training data which include: a text, and marks of a geographic location point and geographic location point spatial relationship information in the text; training a geographic location point spatial relationship extracting model with the second training data, the geographic location point spatial relationship extracting model comprising an embedding layer, a transformer layer and a mapping layer; wherein the geographic location point spatial relationship extracting model is used to extract the geographic location point spatial relationship information from the input Internet text.

Abstract: A POI valuation method, apparatus, device and computer storage medium are disclosed. The method comprises: obtaining information of first POIs with known values and information of second POIs with unknown values within a regional range; creating a valuation model which is configured to revaluate a first POI using values of surrounding POIs of the first POI, the surrounding POIs including other first POIs and second POIs within a predetermined range of distance from the first POI, and adjusting values of second POIs in the surrounding POIs using an error between a revaluated value of first POI and the known value of the first POI; training the valuation model until the error is minimized; obtaining the values of the second POIs from the valuation model. The solutions may reduce the requirement for manpower and improve the valuation efficiency as compared with manually valuation of POIs one by one.

Abstract: According to embodiments of the present disclosure, a method and an apparatus for responding to a question, and a storage medium are provided. The method includes: determining a question characteristic representation corresponding to a question for an object; determining a comment characteristic representation corresponding to a first comment for the object; generating a first target characteristic representation by utilizing the question characteristic representation and the comment characteristic representation; and determining an answer for the question based on the first target characteristic representation.

Abstract: Embodiments of the present disclosure provide a method, an apparatus, a device and a storage medium for evaluating quality of an answer. The method includes extracting a question feature expression of a question and an answer feature expression of an answer with respect to the question, the question and the answer being represented in a form of text; determining a measurement of textual quality of the answer based on the answer feature expression; determining a measurement of correlation on semantics between the question and the answer based on the question feature expression and the answer feature expression; and determining a quality score of the answer with respect the question based on the measurement of textual quality and the measurement of correlations. Therefore, a high-quality answer may be accurately obtained.