Korea Advanced Institute of Science and Technology

International Business Machines Corporation

Chin-Wan Chung

Dragutin Petkovic

Xiaoming Zhu

Deok-Hwan Kim

Seok-Ju Chun

Seok-Lyong Lee

Guang-Ho Cha

Jun-Ki Min

Ju-Hong Lee

Ji-Hyun Lee

Kyuseok Shim

Myung-Jae Park

A semantic search system using a semantic ranking scheme including: an ontology analyzer analyzing ontology data related to a search target to determine a weight value of each property according to a weighing method for property; a semantic path extractor extracting all the semantic paths between resources and query keywords and determining a weight value of each extracted semantic path according to the semantic path weight value determination scheme by using the weight value of each property; a relevant resource searcher traversing an instance graph of ontology based on a semantic path having a pre-set length and weight value of more than an expectation level to search resources that have a semantic relationship with the query keywords and are declared as a type presented in the query; and a semantic relevance ranker selecting a top-k results having the highest rank from among the candidate results extracted by the relevant resource researcher by using a relevance scoring function.

Semantic search system using semantic ranking scheme

Vectors representing objects in n-dimensional space are approximated by local polar coordinates on partitioned cells of the data space in response to a query, e.g., a query data vector entered with a request to find 'k' nearest neighbors to the query vector. A set of candidate near neighbors is generated using the approximations, with the local polar coordinates being independent of the dimensionality of the data space. Then, an answer set of near neighbors is returned in response to the query. Thus, the present invention acts as a filter to reduce the number of actual data vectors in the data set that must be considered in responding to the query.

Indexing system and method for nearest neighbor searches in high dimensional data spaces

A method and apparatus for performing queriable XML compression and queries related to a compressed XML document are disclosed. In the method, information, including at least the frequencies of the respective tags of XML data, the type information of data values and data value-related statistical information is collected. Thereafter, the type information of data values of elements is inferred according to tags using an automatic data type inference engine algorithm. Reverse arithmetic encoding is performed on the tags and paths of elements. The data values are encoded based on the inferred type information.

Method of performing queriable XML compression using reverse arithmetic encoding and type inference engine

A method of processing a query about an Extensible Markup Language (XML) data. The XML query processing method includes the first step of representing the XML data in the form of an XML graph, the second step of creating and updating an Adaptive Path indEX (APEX) based on frequently used paths extracted from previously processed XML queries and the XML graph, and the third step of processing an XML query using the APEX. The XML query processing is capable of improving the performance of processing the query by extracting frequently used paths from path expressions having been used as queries for XML data and updating the APEX through the use of the frequently used paths.

Method of processing query about XML data using APEX

Disclosed herein is a dynamic update cube and hybrid query search method for range-sum queries. The present invention relates to a hybrid query search method, which provides a precise answer or an approximate answer with respect to On-Line Analytic Processing (OLAP) queries by using a delta (&#x394;)-tree, which has a multidimensional index structure and a prefix-sum cube, so as to effectively support range-sum queries widely used in opinion decisions in enterprises. In the dynamic update cube and hybrid query search method for range-sum queries, a prefixed-sum cube is dense and the dynamic update cube is sparse, such that whenever a data cube changes, the prefixed sum cube is not directly updated and instead, the changes of the data cube are stored in a &#x394;-Tree and the &#x394;-Tree is managed.

Dynamic update cube and hybrid query search method for range-sum queries

An apparatus and method for performing similarity searches using hyper-rectangle based multidimensional data segmentation partitions a data set representable by a multidimensional data sequence, such as a video stream, into segments in consideration of the temporal relationship between points, and groups similar segments in one sequence into the same cluster so as to efficiently search a database for a multidimensional data sequence similar to a given query sequence.

Apparatus and method for hyper-rectangle based multidimensional data segmentation and clustering

Disclosed herein is an apparatus and method for similarity searches using hyper-rectangle based multidimensional data segmentation. The similarity search apparatus has MBR generation means, first sequence pruning means, second sequence pruning means, and subsequence finding means. The MBR generation means segments a multidimensional data sequence to be partitioned into subsequences, and represents each subsequence by each Minimum Bounding Rectangle (MBR), such that sets of MBRs are generated from the multidimensional data sequence, and the MBR sets are stored in a database. The first sequence pruning means prunes irrelevant data sequences using a distance D between MBRs extracted from an inputted query sequence and the MBR sets stored in the database in a multidimensional Euclidean space. The second sequence pruning means prunes irrelevant data sequences using a normalized distance D between MBRs extracted from the query sequence and the MBR sets of data sequences remaining after the data sequences are pruned in a multidimensional Euclidean space. The subsequence finding means detects subsequences similar to the given query sequence by obtaining sets of points contained in MBRs involved in a calculation of the distance D from each sequence obtained using the distance D .

Apparatus and method for similarity searches using hyper-rectangle based multidimensional data segmentation

Disclosed is a multi-dimensional selectivity estimation method using compressed histogram information which the database query optimizer in a database management system uses to find the most efficient execution plan among all possible plans. The method includes the several steps to generate a large number of small-sized multi-dimensional histogram buckets, sampling DCT coefficients which have high values with high probability, compressing information from the multi-dimensional histogram buckets using a multi-dimensional discrete cosine transform(DCT) and storing compressed information, and estimating the query selectivity by using compressed and stored histogram information as the statistics.

Growing community of inventors

Taejon, South Korea

Chin-Wan Chung