Interest point display method and device
A technology of points of interest and nouns, applied in the field of display methods and devices of points of interest, can solve problems such as inability to understand meanings, and achieve the effect of improving accuracy
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example 1
[0099] Specifically, it can support the limitation of nearby range based on latitude and longitude. Take the technical implementation of the functional sentence "bus station near Hisense Building" as an example, determine the type of demand through the short text classification algorithm, and extract the first noun "Hisense Building" and the second noun "Bus station", according to the related word "nearby", the matching sentence template is "*2 near *1", and the extracted "Hisense Building" and "bus station" are added to the sentence template and passed to the post At the end, search the range with the location of "Hisense Building" as the center, determine all bus stops within the search range with a certain step size, and gradually expand the search radius until the searched bus stop is found.
[0100] Taking the technical realization of the functional sentence pattern "the nearest subway to Hisense Building" as an example, the demand is judged through the short text classifi...
example 2
[0107] Specifically, attribute restrictions based on business districts / administrative regions can be supported. Taking the technical implementation of the functional sentence "What are the Japanese-flavored stores in the Licang business district" as an example, the short text classification algorithm is used to determine the type of demand and extract the first noun "" Licang business circle" and the second noun "Japanese food flavor store", the distance relation word is the implied relation word "nei". The matching sentence template is found to be "*1*2", and the extracted "Licang business district" and "Japanese food store" are passed to the backend, and the backend calls the retrieval corresponding to the sentence template The specific process is as follows:
[0108] Retrieve the POI entities included / connected (that is, within the search distance) of the first point of interest "Licang business circle", find out the POI store whose flavor type is Japanese cuisine, and ret...
example 3
[0112] Specifically, it can support the limitation based on roads, intersections, and scope. Taking the technical realization of the functional sentence "what are the pharmacies on Ningxia Road" as an example, the short text classification algorithm is used to determine the type of demand, and the first noun "Ningxia Road" and the second noun are extracted. For the noun "drugstore", the relative word representing the distance relationship is "上", "上" is a fuzzy distance word, and the matching sentence template is found to be "*2 on *1", and "Ningxia Road" and "Drugstore" is passed to the backend, and the backend invokes the search method corresponding to the sentence template to search and query. The specific process is as follows:
[0113] Based on the extraction of "Nanjing Road" and "pharmacy", the backend searches for the entity "Nanjing Road" in the knowledge map, and finds the POI connected to the entity within the retrieval distance, selects the entity whose type is phar...
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