Abstract: Methods and system are disclosed that compress a dataset and optimize the dataset for searching data. In one aspect, based on attributes associated with a unified dataset, the dataset including sensor node identifier data, sensor node timestamp data and sensor measurement data are determined. A suffix tree algorithm may be executed to determine data compression logic to compress the dataset including the sensor node identifier data and sensor node measurement data. A sensor node timestamp data compression model may be executed to compress the dataset associated with the sensor timestamp data. The compressed datasets including the sensor node identifier data, the sensor node timestamp data and the sensor measurement data may be stored in an in-memory data store.

Abstract: Methods and system are disclosed that optimize attribute vectors to search for data. In one aspect, a reordering optimization model is executed to reorder the attribute vectors. The attribute vectors may include value identifiers associated with data. The attribute vectors are assigned priorities, sequence score corresponding to each attribute vector is computed and the attribute vectors are reordered based on the computed sequence score. The reordered attribute vectors are logically partitioned into attribute vector blocks by executing a partitioning optimization model. The attribute vector blocks may be generated upon executing the partitioning optimization model. The value identifiers in the attribute vector blocks may be rearranged to optimize the attribute vectors to search for data.

Abstract: Various embodiments of systems and methods for optimizing in-memory column based database table compression. A system may receive a parsed in-memory columnar database table as an input and reads an aggregated compression score from memory corresponding to the parsed database table. A total compression score may be computed iteratively for the database table in order to determine whether the total compression score is greater than the aggregated compression score. When the total compression score determined to be greater than the aggregated compression score, the aggregated compression score is assigned to a best compression score. To optimize in-memory database table compression, the given database table may be compressed using the best compression score.

Abstract: Database searching is optimized utilizing a graph community structure. A graph is created from transaction data based upon adjacent value occurrences. This may be done by scanning transaction data from top to bottom, and creating an edge between a current index value and a previous index value. Next, algorithms identify communities in the graph to create a graph community structure. These communities comprise blocks of patterns of similar value-ids distributed in the transaction data. Scanning and transition indices may be created with an eye toward reducing memory usage and enhancing performance. Query searching is then executed in an efficient manner on a per-community basis. For example, exact queries, range queries, and/or “AND” queries may be executed more efficiently upon communities of records, skipping those not belonging to the same community. Embodiments are suited to search an in-memory database having large volumes of column-oriented data stored in RAM.

Abstract: Methods and system are disclosed that relate to optimizing search for data. In one aspect, an attribute vector may include unique value identifiers and be associated with a dictionary structure. For a unique value identifiers stored in an attribute vector and associated with the dictionary structure, start address and end address associated with the unique value identifiers is computed. Based on the computation, a range of positional addresses associated with the unique value identifiers may be generated and stored in a data structure. Upon receiving a request to search for data, the range of positional addresses in which the unique value identifiers may be searched is determined. Based on the determination, a database search engine optimizes the search for data in the attribute vector.

Abstract: Various embodiments of systems and methods for optimizing in-memory column based database table compression. A system may receive a parsed in-memory columnar database table as an input and reads an aggregated compression score from memory corresponding to the parsed database table. A total compression score may be computed iteratively for the database table in order to determine whether the total compression score is greater than the aggregated compression score. When the total compression score determined to be greater than the aggregated compression score, the aggregated compression score is assigned to a best compression score. To optimize in-memory database table compression, the given database table may be compressed using the best compression score.

Abstract: Methods and system are disclosed that generate an execution schedule to optimize a transformation of business. In one aspect, from multiple tables residing in multiple databases and storing business data associate with multiple business management systems, dependencies between the tables may be determined based on attributes associated with the tables. When execution time for transforming business data exists, a decrease time algorithm or a critical path algorithm may be executed to generate execution schedule and to calculate processor idle times during the transformation of business data. Based on the calculated processor idle times, whether or not to execute a local optimization algorithm may be determined. Based on the determination, execution schedule that optimize the transformation of business data may be generated. The transformation of business data may be executed based to the generated execution schedule that optimizes a time consumed for transforming the business data in the tables.

Abstract: Methods and system are disclosed that compress a dataset and optimize the dataset for searching data. In one aspect, based on attributes associated with a unified dataset, the dataset including sensor node identifier data, sensor node timestamp data and sensor measurement data are determined. A suffix tree algorithm may be executed to determine data compression logic to compress the dataset including the sensor node identifier data and sensor node measurement data. A sensor node timestamp data compression model may be executed to compress the dataset associated with the sensor timestamp data. The compressed datasets including the sensor node identifier data, the sensor node timestamp data and the sensor measurement data may be stored in an in-memory data store.

Abstract: Methods and system are disclosed that optimize attribute vectors to search for data. In one aspect, a reordering optimization model is executed to reorder the attribute vectors. The attribute vectors may include value identifiers associated with data. The attribute vectors are assigned priorities, sequence score corresponding to each attribute vector is computed and the attribute vectors are reordered based on the computed sequence score. The reordered attribute vectors are logically partitioned into attribute vector blocks by executing a partitioning optimization model. The attribute vector blocks may be generated upon executing the partitioning optimization model. The value identifiers in the attribute vector blocks may be rearranged to optimize the attribute vectors to search for data.

Abstract: Methods, apparatus, systems, and computer program products for utilizing a split dictionary are described. A mean and a standard deviation of a length of a plurality of records in a dictionary may be computed. A split condition may be determined based on the computed mean and the computed standard deviation. The dictionary may be split into a plurality of split dictionaries based on the split condition.

Abstract: Database searching is optimized utilizing a graph community structure. A graph is created from transaction data based upon adjacent value occurrences. This may be done by scanning transaction data from top to bottom, and creating an edge between a current index value and a previous index value. Next, algorithms identify communities in the graph to create a graph community structure. These communities comprise blocks of patterns of similar value-ids distributed in the transaction data. Scanning and transition indices may be created with an eye toward reducing memory usage and enhancing performance. Query searching is then executed in an efficient manner on a per-community basis. For example, exact queries, range queries, and/or “AND” queries may be executed more efficiently upon communities of records, skipping those not belonging to the same community. Embodiments are suited to search an in-memory database having large volumes of column-oriented data stored in RAM.

Abstract: An attribute vector including value identifiers and corresponding to a dictionary structure is identified. A dictionary type encoding structure is generated by virtually partitioning the dictionary structure. The dictionary type encoding structure may include multiple dictionary types. Based on the dictionary encoding structure, the attribute vector may be split to generate multiple attribute vector blocks that may be identified by block transition indices. Based on the dictionary types in the dictionary encoding structure, the value identifiers in the attribute vector blocks are rearranged. Such a rearrangement optimizes the attribute vector for searching the value identifiers.

Abstract: Methods and system are disclosed that support optimization for markdown in retail domain to generate an optimized price for a product. The markdown optimization is mapped to a genetic algorithm. In one aspect, an initial population of candidate solutions initializes the execution of the genetic algorithm. Based on a fitness function associated with an objective, the genetic algorithm iteratively executes on the initial population of candidate solutions to compute a fitness score corresponding to each candidate solution. In another aspect, based on the fitness score, the candidate solutions are selected to breed or generate candidate solutions for next-generation. The genetic algorithm terminates when a termination condition is met and may generate a set of particularly desirable result set. In yet another aspect, particularly desirable result set is validated by applying constraints and the validated particularly desirable result set represents most desirable result set.

Abstract: Methods, apparatus, systems, and computer program products for utilizing a split dictionary are described. A mean and a standard deviation of a length of a plurality of records in a dictionary may be computed. A split condition may be determined based on the computed mean and the computed standard deviation. The dictionary may be split into a plurality of split dictionaries based on the split condition.

Abstract: Automated mapping of part numbers associated with parts in a bill of materials (BOM) submitted by a BOM originator to internal part numbers assigned to those parts by a BOM receiver is performed by one or more computers connected to one or more networks through one or more network interfaces. A first receive component receives one or more data sets containing historical data on bills of materials received in the past by the BOM receiver. A second receive component receives one or more data sets containing known mappings between internal part numbers used by the BOM receiver, and part numbers used by various BOM originators. A third receive component receives one or more data sets containing information of various parameters and their values describing the parts to which the BOM receiver has assigned internal part numbers.

Abstract: Automated mapping of part numbers associated with parts in a bill of materials (BOM) to internal part numbers assigned by a BOM receiver. Historical data on bills of materials, known part number mappings, and parametric data describing the parts associated with bills of materials re received. Prediction models, for predicting BOM receiver internal part numbers, are learned from the historical BOM data, known part number mappings data and parametric data. The learned models are applied to unmapped BOM originator part numbers to assign BOM receiver internal part numbers.

Abstract: Automated mapping of part numbers associated with parts in a bill of materials (BOM) submitted by a BOM originator to internal part numbers assigned to those parts by a BOM receiver is performed by one or more computers connected to one or more networks through one or more network interfaces. A first receive component receives one or more data sets containing historical data on bills of materials received in the past by the BOM receiver. A second receive component receives one or more data sets containing known mappings between internal part numbers used by the BOM receiver, and part numbers used by various BOM originators. A third receive component receives one or more data sets containing information of various parameters and their values describing the parts to which the BOM receiver has assigned internal part numbers.

Abstract: Automated mapping of part numbers associated with parts in a bill of materials (BOM) submitted by a BOM originator to internal part numbers assigned to those parts by a BOM receiver is performed by one or more computers connected to one or more networks through one or more network interfaces. A first receive component receives one or more data sets containing historical data on bills of materials received in the past by the BOM receiver. A second receive component receives one or more data sets containing known mappings between internal part numbers used by the BOM receiver, and part numbers used by various BOM originators. A third receive component receives one or more data sets containing information of various parameters and their values describing the parts to which the BOM receiver has assigned internal part numbers.

Abstract: An interactive bid evaluation system (method and storage medium) for a combinatorial auction, includes a display for scaling a plurality of bids and items, on a display window.