48 results about "Cartesian product" patented technology

A system, apparatus, and program storage device implementing a method of optimizing queries used for searching a computerized database, wherein the method comprises providing a query comprising a sequence of inner joins and outerjoins; and rewriting the query by producing a sequence of outer Cartesian products for the query; producing a sequence of nullification operations on the query; and producing a sequence of best match operations on the query. The method further comprises optimizing the query using a query execution plan for processing the rewritten query, wherein the query execution plan expands a search space in the database for which the rewritten query may be run.

The invention discloses a Chinese text verification system and method based on Chinese vague pronunciation and voice recognition. The system comprises a voice collecting and processing module, a voice recognition module and a text verifying and sharing module, wherein the voice collecting and processing module is used for collecting an audio and compressing and denoising the audio, the voice recognition module is used for recognizing voices into a text, and the text verifying and sharing module is used for achieving text verification and meanwhile supports text editing and sharing. The method comprises the steps that Chinese error judgment rules based on parts of speech are defined; word segmentation is carried out on the Chinese text obtained after voice recognition; the segmented words are scanned according to the Chinese error judgment rules to find out wrong Chinese words; a vogue pronunciation table is defined based on Chinese vogue pronunciation rules; all vogue pinyin of the wrong words is found out through a Cartesian product mode; a dictionary table is inquired to obtain a candidate word set of all the vogue pinyin; a candidate error correction set is selected out of words of the candidate set of all the vogue pinyin according to a word frequency rank. By means of the Chinese text verification system and method based on Chinese vague pronunciation and voice recognition, Chinese errors, caused by Chinese vogue pronunciation, in voice recognition are eliminated, and the error correction accuracy rate of a verification algorithm is effectively increased.

A system, apparatus, and program storage device implementing a method of optimizing queries used for searching a computerized database, wherein the method comprises providing a query comprising a sequence of inner joins and outerjoins; and rewriting the query by producing a sequence of outer Cartesian products for the query; producing a sequence of nullification operations on the query; and producing a sequence of best match operations on the query. The method further comprises optimizing the query using a query execution plan for processing the rewritten query, wherein the query execution plan expands a search space in the database for which the rewritten query may be run.

A storage robot path program method based on linear temporal logic theory comprises the steps of modeling a storage environment into a weight switching system based on assignment nodes; describing complex assignment tasks of the storage system by using the linear temporal logic language (LTL); then, switching the task formula into a Buchi automatic machine through an LTL2BA tool kit; conducting cartesian product to the extensible weight switching system and the Buchi automatic machine to form a task feasible network topology; employing SPFA(Shortest Path Faster Algorithm) on the topology to search an optimal path, wherein the task feasible network topology includes storage environment information and package-taking task information, guaranteeing that the searched obtained path is the optimal path and isn't influenced by the order of the selected assignment node; mapping the obtained optimal path from the task feasible network topology to the corresponding optimal path in the storage environment, and sending the optimal path to a storage robot by radio communication through a PC to finish the packaging-taking and assignment task.

The invention relates to an integration method for depth feature and traditional feature based on AdaRank. The main technical characteristics comprise: dividing image data, respectively establishing aimed at different parts and training a depth convolution and a neural network, used to obtain depth features; extracting traditional features from pedestrian re-identification data, including LOMO features, ELF6 features, and Hog3D features; selecting the following three metric learning methods, KISSME, kLFDA, and LMNN; all the features and the three metric learning methods being combined and spanned to a Cartesian product, to obtain a series of weak sorters; using an AdaRank algorithm, performing ensemble learning on the weak sorters, to finally obtain a strong sorter. The method is reasonable in design, and combines depth learning, multi-feature, metric learning, and ensemble learning, and learns in an integrated manner through establishing the weak sorters, so integrated performance of a system is much better that using a single feature and a single metric learning, system integrated matching ratio is greatly improved, and good performance is obtained.

The invention discloses a test case generation method and a test case generation device. The method includes: acquiring test dimensional items which are collections containing valid equivalence classes and invalid equivalence classes, acquired by partitioning test dimensions in advance with an equivalence partition method; generating to-be-selected test cases according to the test dimension items by mean of a Cartesian product method; according to a preset simplification rule, removing the redundant to-be-selected test cases to acquire the final test cases. The test dimensions are partitioned by the aid of the equivalence partition method, a great deal of redundancy in the test cases can be reduced, the to-be-selected test cases are further simplified according to the simplification rule, and less redundancy in the final test case is achieved; the to-be-selected test case collections are generated by the aid of the Cartesian product method, and cover degree of the test cases can be guaranteed; less redundancy and high cover degree of the test cases are achieved, and test coverage and test quality can be improved on the basis of limited case cost.

The invention discloses a synonym expansion method and a synonym expansion device both used for text duplication detection, which include a text preprocessing unit used for deleting stop words in a suspected text and tagging the part-of-speech, wherein verbs, nouns, and adjectives are taken as the to-be-processed objects; through retrieving synonyms of single words, computing the Cartesian product and obtaining the initial expansion set of all word collocations in the suspected text; through comparing the initial expansion set and an actual corpus, filtering word collocations impossible in an actual language environment, simplifying the set, and obtaining the final expansion set; and during the duplication detection, according to different collocation results, giving the words different weights which are taken as the computation base for the duplication detection results. Through applying the method or the device disclosed by the embodiment of the invention, the problem of synonym replacement in text duplication can be efficiently overcome, the efficiency is higher, and the accuracy of the duplication detection is greatly improved.

The invention relates to the field of intelligent driving, specifically discloses a driving assistance system-oriented dangerous target detection method and device, and aims at solving the problem oflow dangerous target detection precision under field complicated traffic scenes. For the aim, the dangerous target detection method comprises the following steps of: identifying a detection frame position of a dangerous target in an obtained vehicle body external image and a Cartesian product of a target type and a distance type according to a preset dangerous target detection model; obtaining a danger level of the target according to the Cartesian product and a danger level matching table; and marking a detection frame of the target in the image according to a color corresponding to the danger level. Meanwhile, the dangerous target detection device, a dangerous target storage device and a dangerous target processing device can execute the steps in the dangerous target detection method. Through above technical scheme, the accuracy of image-based dangerous target detection can be enhanced under real complicated traffic scenes, so as to prevent traffic accidents.

Design spaces for systems, including hierarchical systems, are programmatically validity filtered and quality filtered to produce validity sets and quality sets, reducing the number of designs to be evaluated in selecting a system design for a particular application. Validity filters and quality filters are applied to both system designs and component designs. Component validity sets are combined as Cartesian products to form system validity sets that can be further validity filtered. Validity filters are defined by validity predicates that are functions of discrete system parameters and that evaluate as TRUE for potentially valid systems. For some hierarchical systems, the system validity predicate is a product of component validity predicates. Quality filters use an evaluation metric produced by an evaluation function that permits comparing designs and preparing a quality set of selected designs. In some cases, the quality set is a Pareto set or an approximation thereof.

The invention discloses an English word relevancy calculating method and device based on Wikipedia concept vectors. The method comprises the steps that 1, a Wikipedia Dump service site obtains raw linguistic data and performs standardized processing to generate a Wikipedia basic corpus; 2, concept labeling and extension are performed, and a Wikipedia concept corpus is established; 3, according to the Wikipedia concept corpus, the concept vectors are trained; 4, for word pairs to be compared, a word concept set is obtained according to Wikipedia; 5, the similarity of the concept vector corresponding to each concept in Cartesian products of the concept set is calculated, and a maximum value is taken as the relevancy of the word pairs to be compared. By utilizing the method, word concept information contained by Wikipedia can be fully mined to generate word concept vectors, and word relevancy can be more accurately and effectively calculated.

According to an aspect of the inventive concept, there is provided a system for detecting vulnerabilities of communication protocol software, including: a field selection module selecting message fields of a communication protocol of an industrial control system; a value set configuration module configuring first value sets with respect to the respective message fields selected by the field selection module; a test case generation module generating first test cases by Cartesian product of the first value sets; a test module generating first code coverage data by testing the communication protocol software of the industrial control system based on the first test cases; and a code coverage analysis module analyzing the first code coverage data, wherein the field selection module selects concentration message fields which influence the first code coverage data among the message fields according to an analysis result of the code coverage analysis module.

The invention relates to a method for searching an optimal execution plan in database query, comprising the following steps: execution plans which contain Cartesian product connection operation are not considered in the execution plan searching process (except that a query statement submitted by a user contains the Cartesian product connection operation); meanwhile, the connection relationship ofa relationship table in the statement is expressed in an image format; and finally, the optimal execution plan is searched in the image. The connection relationship of the statement expressed in the image format is as follows: points in the image represent the relationship in the query statement; two points are connected if the relationship corresponding to the two points in the image contains connection operation (including inner connection and outer connection); and the edge weight is the execution cost of the connection operation of two relationships. By using the structure, the optimal execution plan can be obtained in the concurrent execution environment.

The invention provides a shape matching identification system and the implementation method thereof, aiming at the problems in the prior art after the color and shape identifications are researched. Firstly, a digital camera is adopted to shoot the object adhered with an artificial label for the three-dimensional reconstruction and form the picture of the object; then the shape characteristic and the color characteristic of the picture are extracted through the characteristic extraction module; the shape characteristic and the color characteristic are written into a characteristic vector and normalized through the characteristic vector normalization module; finally, the normalized characteristic vector is recognized by a neural network module. The invention has the advantages that the system and the implementation method adopt the mixed matching method based on color and shape to avoid the gray-scale based matching and the multiple repeated matching acknowledgements with large computational complexity; based on the Cartesian product combination of the angle point number characteristic in the color category and the space characteristic, the artificial label point characteristics with enough quantity are generated to enable the matching operation to be finished in one-step, so as to improve the matching efficiency greatly.

The invention provides a query log-based database statistic data histogram generation method, which comprises the following steps of: 1) extracting a query set from a database query log, making query of each time corresponding to an attribute, and forming an array by using left and right boundary values of an attribute set; 2) sequencing the array, and generating basic intervals consisting of adjacent dotted pairs; 3) calculating Cartesian products of the intervals on different attributes to form cubes; 4) obtaining density values of the cubes according to a result row number obtained by the query of each time and the Cartesian products of the cubes; and 5) generating a histogram according to the density values of the cubes. The method provided by the invention is used for generating the histogram based on the database query log, and solves the problems that a conventional database system generates the histogram by scanning raw data to cause high cost and that the conventional method for incrementally generating the histogram by utilizing the query log causes great errors.

The invention can be applicable to the field of data processing and provides a method, device and terminal for generating a multi-dimensional dynamic data sheet. The method comprises the following steps: receiving one or multiple consideration dimensions defined by a user, wherein the consideration dimension includes one or more consideration dimension levels; receiving one or more data dimensions defined by the user, wherein the data dimension includes one or more data dimension levels; with dynamic data as a data row and the data dimension levels of the data dimensions as a data expansion line, generating a multi-dimensional dynamic data sheet according to the defined consideration dimensions and data dimensions, wherein the dynamic data is generated by taking the consideration dimension levels of the consideration dimensions as Cartesian product; therefore, the expandability of the data sheet and the generation efficiency of the data sheet can be effectively improved.

The invention discloses a theta-join method for massive distributed data, which is used for solving the technical problem of low efficiency of the conventional theta-join method. The method adopts the technical scheme that prior to theta-join of two tables, appropriate filtering rules are firstly selected according to join conditions, the maximum values and the minimum values of join fields of the two tables are then calculated, all records in the two tables are scanned according to the maximum values and the minimum values, the records irrelevant to output results are removed through filtering, Cartesian product calculation is only carried out for filtered data, and a secondary comparison of Cartesian product results is finally carried out according to the join conditions, so that the records satisfying the join conditions are obtained through screening. The method has the advantages that a large number of the records which fail to satisfy the join conditions are removed through the filtering prior to the Cartesian product calculation, so that the workload of a Reducer is effectively reduced, and the theta-join query efficiency is improved.

The invention discloses a cross-social media account matching method which integrates social relations and naming characteristics. The method comprises the following steps: S1, finding out the users corresponding to the accounts of other platforms in the account information as a set of seed users; S2, extracting a pair of account information from the seed user set, respectively extracting the account number of a friend in the corresponding platform, and making a Cartesian product as a candidate account pair; S3, carrying out pretreatment to obtain features to form feature vector; S4, inputtingthe feature vector into the classifier for judging, and adding the account judged to belong to the same person entity into the seed node set; S5, performing the operations of steps S2 to S4 on all the seed nodes until no new account is added in the seed user set. The method of the invention reduces the computational complexity, and the calculation of the extracted features of the users which arefinally judged to be unrelated and carried out classification judgment is called invalid calculation, which greatly reduces the proportion of invalid calculation in the whole calculation process and improves the efficiency.

The invention discloses a method for globally presenting IT infrastructure data in a CMDB, and the method includes the following steps: S1), acquiring the data of configuration items, each two of which are correlated, in the CMDB; S2), performing a Cartesian product operation of the association data acquired from the CMDB, and expanding the service topology by using a service system as a source; S3), verifying the integrity and accuracy of the association data with built-in validation rules, discovering topology breakpoints and summarizing the topology breakpoints. The method performs the Cartesian product calculation of the CMDB association data, generates a complex data list, analyzes and views the global view, grasps the IT architecture, and discovers the data quality problems existingin the IT architecture, thereby facilitating maintenance personnel to improve data, improving the data quality, and providing the basis for hardware maintenance.

The invention discloses a Chinese word relevancy calculation method and device based on Wikipedia concept vectors. The method comprises the steps that 1, a Wikipedia Dump service site acquires raw corpora, conducts normalized treatment on the raw corpora and generates a Wikipedia basic corpus; 2, concept labeling and expanding are conducted, and a Wikipedia concept corpus is built; 3, according to the Wikipedia concept corpus, the concept vectors are trained; 4, according to the Wikipedia, a word concept set of word pairs to be compared is acquired; 5, the similarities of the concept vectors corresponding to all the concept pairs in the cartesian product of the concept set are calculated, and the largest value is used as the similarity of the word pairs to be compared. By using the Chinese word relevancy calculation method and device based on the Wikipedia concept vectors, word concept information which is contained in the Wikipedia can be sufficiently excavated so that the word concept vectors can be generated, and the word similarity can be calculated more accurately and effectively.

The optimal strategy solution of mobile robot in dynamic environment includes the following steps: Firstly, according to the running environment of the robot, the improvement is constructed. Weightedswitching system, according to the task requirements, the task requirements are expressed mathematically by linear temporal logic (LTL), and the LTL task formulas are transformed into B u chi automataby LTL2BA toolkit. Then Cartesian product is used to get Product automata, which contains task requirement and environment information. The useless points on the feasible network topology graph are removed, and the availability of state points is further judged according to the double-label and behavior constraint criterion, thus the number of state points is simplified. The remaining points areconstructed as MDP model, and the optimal strategy is obtained by policy iteration. The invention not only solves the situation that there is no DRA, but also reduces the number of available points, reduces the complexity of the constructed MDP, and can obtain the optimal strategy more quickly.

The invention provides a screening method of attribute combination. The screening method includes setting multiple attribute value dependency groups of data entity according to received setting commands; splitting each of the attribute value dependency groups and performing Cartesian product combination on a first value range and a second value range of a first attribute set and a second attribute set to obtain multiple attribute value dependence value groups, and sequencing split results according to a preset sequencing manner to obtain an attribute combination effectiveness definition list. Each attribute value dependence value group includes one first value range of one attribute information and one second value range of the corresponding second attribute information. The invention further provides a screening device of attribute combination correspondingly. According to the technical scheme, the screening method can assist users to screen effective attribute combinations within a short time, reduce operation complexity and bring good experiences to the users.

The embodiment of the invention relates to the technical field of data processing. In particular, the invention relates to a camera, The invention relates to a two-dimensional density clustering method and device. The method comprises the following steps: selecting a plurality of two-dimensional coordinate points for Cartesian product connection on a first sample obtained by random selection; Therefore, parallel clustering calculation of each two-dimensional coordinate point is achieved, traditional full traversal is modified into parallel traversal, multi-thread multi-process concurrent execution of class cluster division is achieved, calculation time can be effectively shortened, and calculation efficiency is improved.

The invention provides a method for analyzing the stability of a structural system under an uncertain information condition. The method comprises the following steps of (A) establishing a stability equation D=Func(x1, x2, ..., xi, ..., xn) of the structural system; (B) performing probability box modeling on uncertain information parameters in the structural system; (C) performing equal reliabilitydiscretization on probability boxes of the uncertain information parameters; (D) substituting the uncertain information parameters into the stability equation of the structural system and calculatinga Cartesian product; (E) obtaining a probability box model of a complete system; (F) defining a stability region and a risk region of the system; and (G) calculating areas of the corresponding regions to quantitatively analyze the stability of the structural system. The method has the beneficial effects that the probability boxes are adopted for expressing the uncertainty; not only random uncertainty of the parameters in the system but also cognitive uncertainty can be expressed; the problem of parameter uncertainty in the system model is better solved; and the stability of the structural system is analyzed in combination with the method, so that the accuracy of analyzing the stability of the structural system is improved.

The invention discloses a combined-feature extraction method of internet-of-vehicle big-data risk control. The method comprises the steps of: obtaining basic data of an internet-of-vehicle user, and generating an initial feature set according to the basic data; calculating Cartesian products of the initial feature set and the same, and generating a second-order combined-feature set; and then extracting second-order combined-features, which are in the second-order combined-feature set and accord with a preset condition, to form a second-order candidate feature set, and calculating Cartesian products of the second-order candidate feature set and the initial feature set to generate a third-order combined-feature set; and further, outputting high-order combined-features, which accord with a preset order number, according to the above iteration process. The invention also discloses a combined-feature extraction device of internet-of-vehicle big-data risk control and a storage medium. The method constructs linear and nonlinear features through a method of obtaining the Cartesian products to improve accuracy of risk control results.

The invention relates to a Lucene-based wrongly written character query method. A sentence of a queried text is subjected to word segmentation; a first word is selected; whether the first word is a single word or not is judged; if the first word is the single word, a similar voice table and a similar shape table are queried; a query result simset is returned according to the similar voice table and the similar shape table; the query result simset and a next word or a query result simset of the next word are subjected to Cartesian product to obtain a Cartesian product result; the result is used to be matched with all words in a dictionary; if the matching succeeds, an error correction result is returned and added to an error correction result set; if the error correction result set is null, a null value is returned and the matching exits; if the error correction result set is not null, all error correction results are returned and used for performing a query; and if the first word in the sentence of the text is not the single word through the query or the matching between the result and all the words in the dictionary fails, characters are read backwards, and the previous steps are repeated. The method has the advantages that Lucene retrieval can be more accurate and humanized; and the retrieval accuracy is improved.

The invention discloses a dynamic asset pool construction method with a self-feedback function, which mainly includes the following steps: obtaining a feature vector of a target asset pool through an asset screening module using a Cartesian product algorithm, and converting the vectorized assets into the asset package Match with it, supplement the size of the asset pool that is lost due to repayment every day, push the asset package to be put into the pool, mark the asset package that has been pushed, and then clear the feature vector of the assets that have not entered the asset package to be put into the pool; this method adopts A model combining Cartesian product and independent random events is used to satisfy the dynamic asset pool, keeping the size and structure of the asset pool consistent with the size and structure of the asset pool set by the target, and the system can automatically feedback the existing size and structure of the asset pool to converge depends on the size and structure of the target asset pool.

The invention discloses an on-line number of people distribution calculation method and device, and belongs to the field of on-line live broadcast. The method includes the steps: obtaining on-line time periods of each user corresponding to different types of client sides in an Internet product; for the on-line time periods of each user corresponding to different types of clients which intersect, splitting according to intersection endpoints to obtain split time periods of each user under different on-line types; and according to the split time periods of each user under different on-line types, calculating on-line number of people statistical data corresponding to a certain type of clients. The method solves the problems that when on-line number of people statistical data corresponding to different types of clients are calculated, the calculation quantity is enormous, and calculation is time-consuming; and the effects of avoiding a Cartesian product and a large amount of duplicate removing calculation in a calculation process, simplifying data when distribution situations of the on-line number of people on different types of client is calculated, reducing the calculated amount of calculation data, and improving algorithm operation efficiency are achieved.