A computer system is configured to receive a plurality of previous user selections by a user of previous database entries, each of which has as plurality of database field. The computer system is configured to determine weights for the various database fields included in the previous user selections and rank subsequent search results for a subsequent search of the database based on the determined weights, where the one or more weights affect a ranking of a search result based on a match associated with the particular database field. The computer system is further configured to receive customized search result layout settings specifying that one or more specified database fields are displayed to the user when the search results are displayed, where one or more weights for the particular database field are based on the customized search result layout settings.

A display apparatus (1) includes a searcher (105) that searches document data displayed on a display device (10) for a target character that accords with a character to search, and a marker display controller (106) that displays a marker on a position corresponding to the target character detected by the searcher (105). A display controller (103) (i) causes the display device, when a slide operation is performed on the marker displayed on the display device (10), to display a next marker on an opposite side, in a direction of the slide operation, and (ii) causes the display device, when a slide operation is performed on a position other than the marker displayed on the display device (10), to scroll a screen on the display device (10) in the direction of the slide operation.

Unauthorized use of user credentials in a network is detected. Data indicative of text strings being used to access resources in the network is accessed. Regex models are determined for the text strings. Groupings of the regex models are determined based on an optimization of a cumulative weighted function. A regex model having a cumulative weighted function that exceeds a predetermined threshold is identified. An alert is generated when the cumulative weighted function for the identified regex model exceeds the predetermined threshold.

A system described herein may provide a technique for the compression of query terms and search data against which the query terms may be evaluated. The compression may be dynamic, in that a quantity of bits used to compress the search data and query terms may be based on a quantity of unique characters included in a given query term. The compression may further include reducing the volume of search data by compressing entire words, that do not include any of the unique characters of the query term, to one particular code.

Methods, systems, and computer programs are presented for automatically generating phrase-based talent-screening questions. One method includes analyzing job descriptions to generate ngrams. Each ngram comprises one or more words. Further, the method includes identifying, from the ngrams, an ngram set comprising a predetermined number of bigrams and trigrams according to frequency of appearance in the job descriptions. The method further includes removing, from the ngram set, bigrams and trigrams comprising one or more of stop words, negation words, or requirement words, to obtain first seed phrases. The first seed phrases are filtered based on a frequency of appearance of the seed phrase in the job descriptions to obtain second seed phrases. Further, the second seed phrases are added to the first seed phrases to obtain third seed phrases. Each seed phrase is a sequence of one or more words that is associated with a category of talent-screening questions.

The present disclosure provides an error correction method. The error correction method includes: determining a plurality of target candidate entities from a preset dictionary tree based on a query request; for each target candidate entity, calculating a first probability that the target candidate entity is a legitimate entity; evaluating each target candidate entity to obtain an evaluation result, a target candidate entity corresponding to an evaluation result; and determining a real intent entity corresponding to the query request based on the first probability and the evaluation result.

An instruction is provided for performing a vector string search. The instruction to be processed is obtained, with the instruction being defined to be a string search instruction to locate occurrence of a substring within a string. The instruction is processed, with the processing including searching the string specified in one operand of the instruction using the substring specified in another operand of the instruction. Based on the searching locating a first full match of the substring within the string, a full match condition indication is returned with position of the first full match in the string, and based on the searching locating only a partial match of the substring at a termination of the string, a partial match condition indication is returned, with the position of the partial match in the string.

Technology is described herein for ranking candidate result items in at least two stages. In a first stage, the technology uses a first attention-based neural network to determine an extent of attention that each token of an input query should pay to the tokens of each candidate result item. In a second stage, the technology uses a ranking subsystem to perform listwise inference on output results provided by the first stage, to generate a plurality of ranking scores that establish an order of relevance of the candidate results items. The ranking subsystem may use a second attention-based neural network to perform the listwise inference. According to some implementations, the technology is configured to process queries and candidate result items having different kinds and combinations of features. For instance, one kind of input query may include text-based features, structure-based features, and geographic-based features.

A system and method are provided for discovering k-nearest-neighbors to a given point within a certain distance d. The method includes constructing an index of geometries using geohashes of geometries as an indexing key to obtain an indexed set of geometries, and calculating a geohash representation of the given point with a resolution equal to a magnitude value of d. The method includes searching for a closest-prefix geometry from the indexed set using the geohash representation of the given point, and identifying geometries from the indexed set having a same prefix as the closest-prefix geometry. The method further includes calculating distances between the given point and the geometries identified from the indexed set having the same prefix as the closest-prefix geometry, and determining k geometries with respective shortest distances less than d from the geometries identified from the indexed set having the same prefix as the closest-prefix geometry.

Systems and methods for serving subject access requests (SARs) are disclosed. A network connection is established with a user. An SAR, including at least one piece of personal data corresponding to an entity associated with said user, is received from the user via the network connection. Text data is extracted from a plurality of data objects, the data objects including personal data associated with the user. The text data is then processed to identify instances of names and instances of personal data within the text data. Associations are generated between identified names and identified personal data. A subset of the identified personal data that corresponds to the entity is identified based on the associations. A response to the SAR is provided, based at least in part on the identified personal data corresponding to the entity.