Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing a complex KR from the elemental data structure may rely on statistical inference techniques.

Abstract: A computer-implemented method comprising partitioning data representing an input instance of a database including multiple tuples into multiple fragments of tuples, detecting tuples which violate a data quality specification in respective ones of the fragments, selecting a data cleaning asset on the basis of characteristics of errors in detected tuples for a fragment and based on declared asset capabilities, assigning a selected data cleaning asset to the fragment, the selected data cleaning asset to provide a set of candidate corrections for the detected tuples in the fragment, providing data representing an output instance of the database in which detected tuples are replaced with selected candidate corrections.

Abstract: A computer implemented method for repairing records of a database, comprises determining a first set of records of the database which violate a functional dependency of the database, modifying records in the first set to make them consistent with the functional dependency to provide an output consistent database instance, determining a second set of records of the output consistent database instance comprising duplicate records, merging duplicate records in the second set in dependence on the functional dependencies of the records to provide a modified database instance.

Abstract: A method for integrating data into a database comprises storing data comprising a plurality of records which each comprise a plurality of attributes; analysing a sample of records from the plurality of records by: identifying duplicate pairs of records in the sample records; analysing each attribute of each record of the duplicate pairs of records to identify a respective attribute condition which is indicative that the pairs of records are duplicates; wherein the method further comprises: comparing each attribute of a record with the respective attribute condition and, if the attribute satisfies the attribute condition, allocating the record to a disjoint group which comprises records with an attribute that satisfies the same respective attribute condition; identifying duplicate pairs of records in the records in each disjoint group; identifying duplicate pairs of records in records that are not allocated to a disjoint group; and consolidating each duplicate pair of records into one consolidated record and s

Abstract: Methods and system of searching for content in a target set of content based on a reference set of content, a reference semantic network representing knowledge associated with the reference set of content, and a target semantic network representing knowledge associated with the target set of content. Techniques include receiving a user-specified search query, obtaining at least one concept semantically relevant to the user-specified search query by using the target semantic network and the reference semantic network, constructing a second query by augmenting the first search query with one or more terms associated with the at least one obtained concept; providing, to the at least one user, content associated with search results obtained based on searching the target set of content by using the second query, wherein any concept in the semantic network is represented by a data structure storing data associated with a node in the semantic network.

Abstract: A computer implemented method for correcting records in a database comprising generating, using a processor, respective candidate replacement entries for multiple inconsistent records of the database, grouping the candidate replacement entries to provide multiple groups of related candidate updates for the database, ranking the groups according to a loss function to quantify database quality, receiving input for a selected group, sorting candidate replacement entries in the selected group, and applying updates from the selected group to the database to correct entries of the inconsistent records.

Abstract: A computer-implemented method comprising partitioning data representing an input instance of a database including multiple tuples into multiple fragments of tuples, detecting tuples which violate a data quality specification in respective ones of the fragments, selecting a data cleaning asset on the basis of characteristics of errors in detected tuples for a fragment and based on declared asset capabilities, assigning a selected data cleaning asset to the fragment, the selected data cleaning asset to provide a set of candidate corrections for the detected tuples in the fragment, providing data representing an output instance of the database in which detected tuples are replaced with selected candidate corrections.

Abstract: Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules that are machine-readable. The elemental data structure may include a universal kernel and customized modules, which may represent knowledge that is generally applicable to a population and knowledge that is specifically applicable to individual data consumers, respectively. A method of constructing an elemental data structure may include analyzing first information to identify a first elemental component associated with a data consumer, and adding the first elemental component to a customized module corresponding to the data consumer. The method may also include analyzing second information to identify a second elemental component associated with a population, and adding the second elemental component to the universal kernel.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. The elemental data structure may include a universal kernel and one or more customized modules. The universal kernel may represent knowledge that is generally applicable to a population, and the customized modules may represent knowledge that is specifically applicable to individual data consumers. Crowd-sourcing techniques may be applied to the elemental data structure. A method of modifying the elemental data structure may include obtaining an indicator regarding an elemental component based on data associated with customized modules.

Abstract: A computer implemented method for repairing records of a database, comprises determining a first set of records of the database which violate a functional dependency of the database, determining a second set of records of the database comprising duplicate records, computing a cost metric representing a measure for the cost of mutually dependently modifying records in the first and second sets, modifying records in the first and second sets on the basis of the cost metric to provide a modified database instance.

Abstract: A computer implemented method for repairing records of a database, comprises determining a first set of records of the database which violate a functional dependency of the database, modifying records in the first set to make them consistent with the functional dependency to provide an output consistent database instance, determining a second set of records of the output consistent database instance comprising duplicate records, merging duplicate records in the second set in dependence on the functional dependencies of the records to provide a modified database instance.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including an elemental data structure and knowledge processing rules that are machine-readable. The elemental data structure may include a universal kernel and customized modules, which may represent knowledge that is generally applicable to a population and knowledge that is specifically applicable to individual data consumers, respectively. A method of outputting a complex KR may include receiving input from a data consumer. The method may further include applying rules to the elemental data structure. Applying rules to the elemental data structure may include applying a rule to the universal kernel and applying a rule to a customized module. The method may further include synthesizing a concept and/or a relationship based on the application of the rules, and outputting a complex KR that is customized to the data consumer based on the customized module.

Abstract: Disclosed is a system and method for performing a semantic operation on a social network. In an embodiment, the method comprises receiving a social network user context associated with a user of the social network; generating, through a semantic operation, an interest network based on the user context information; and filtering, ranking or augmenting, using at least one processor executing stored program instructions, a retrieval of information related to the social network based on the interest network; wherein the interest network comprises concepts represented by a data structure associated with the concepts in the interest network. In another embodiment, the method further comprises representing the interest network as an interest graph. In yet another embodiment, the semantic operation is a synthesis operation or retrieval operation performed on a knowledge representation.

Abstract: Techniques for obtaining user preferences. The techniques include receiving user context information associated with at least one user; identifying, based at least in part on the received user context information, a plurality of attributes of items in a plurality of items; obtaining, using at least one processor, at least one first-order user preference based at least in part on a first input provided by the at least one user, wherein the plurality of first-order user preferences comprises a preference for a first attribute in the plurality of attributes; and obtaining, using the at least one processor, at least one second-order user preference based at least in part on a second input provided by the at least one user, wherein the at least one second-order user preference comprises a preference among attributes in the plurality of attributes.

Abstract: Techniques for specifying user preferences in a semantic network. The techniques include receiving, using at least one processor, a plurality of first-order user preferences for at least one concept in a semantic network, wherein the plurality of first-order user preferences are indicative of a user's preferences among children of attributes of the at least one concept in the semantic network; receiving, using the at least one processor, at least one second-order user preference for the at least one concept in the semantic network, wherein the at least one second-order user preference is indicative of the user's preferences among attributes of the at least one concept; and performing at least one semantic processing act by using the semantic network, the plurality of first-order user preferences, and the at least one second-order user preference.

Abstract: Techniques for calculating a ranking of at least one item in a plurality of items. The techniques include receiving user preferences comprising a plurality of first-order user preferences indicative of a user's preferences for items in the plurality of items, and at least one second-order user preference indicative of the user's preferences among first-order user preferences in the plurality of first-order user preferences; calculating, with at least one processor, a ranking of the at least one item in the plurality of items based, at least in part on, at least one data structure encoding a preference graph that represents the received user preferences; and identifying and outputting at least a subset of the plurality of items to a user, in accordance with the ranking.

Abstract: A computer implemented method for correcting records in a database comprising generating, using a processor, respective candidate replacement entries for multiple inconsistent records of the database, grouping the candidate replacement entries to provide multiple groups of related candidate updates for the database, ranking the groups according to a loss function to quantify database quality, receiving input for a selected group, sorting candidate replacement entries in the selected group, and applying updates from the selected group to the database to correct entries of the inconsistent records.

Abstract: There is disclosed a system and method for using a knowledge representation to provide relevant information based on environmental inputs. In an embodiment, the system and method considers environmental information from members in a crowd to generate a pool of interests based on the semantic relevance concepts associated with those interests. The most prominent concepts of interest may then be the basis for presenting content to the crowd as a whole. In another embodiment, environmental inputs and other surrounding inputs are considered as a user context. The concepts may be identified as relevant from the environmental context and used to present information relevant to the user given his or her surroundings.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with context information. Methods of populating an elemental data structure and methods of synthesizing a complex KR from the elemental data structure may rely on statistical inference techniques.