Abstract: A method for providing recommendations for customers is described. The method comprises obtaining transaction data associated with one or more products being purchased by a customer. The method further comprises generating a customer household graph, wherein the customer household graph comprises a customer household node associated with the customer, a product superset node, and one or more product nodes associated with the product superset node. Further, at least one product metadata node associated with each of the one or more product nodes is determined. Further, at least one user node is associated with the customer household node based on the at least one product metadata node. Further, a user group node associated with the customer household node is determined based on the at least one user node. Further, one or more recommendations to be provided to the user are ascertained.

Abstract: Knowledge representation in a multi-layered database includes systems and methods for storing and retrieving data in the multi-layered database. The multi-layered database includes an object database layer that stores objects corresponding to real world entities and each object is associated with object properties, object relationships, and relationship properties. Underlying the object database layer is a graph database layer that stores nodes, node properties associated with the nodes, edges, and edge properties associated with the edges, wherein the nodes correspond to objects, node properties are indicative of the object properties, the edges are indicative of the object relationships, and the edge properties are indicative of the relationship properties of the object. Further, underlying the graph database layer is a backend database layer that stores corresponding data and metadata. Data can be stored and retrieved from the multi-layered database by composing and decomposing information between layers.

Abstract: Method(s) and system(s) providing for providing context based conversations are described here. The method may include receiving user data pertaining to a user. The user data includes registration information of the user and metadata associated with the user. The method may include determining a pre-defined role of the user based on the registration information. Further, the method may include providing restricted access to a users' data repository to the user, based on the role of the user. The method includes obtaining a text input pertaining to a conversation. Based on the text input an expression is generated. Further, one of a discussion service, a learning service, and an unlearning service is invoked, based on the expression and the metadata associated with the user. Based on at least one of the invoking services and the metadata associated with the user, retrieving a response. The response is shared with the user.

Abstract: Knowledge representation in multi-layered database includes systems and methods for storing and retrieving data in the multi-layered database. In the multi-layered database, an action graph database includes participant-entity nodes corresponding to real world entities and action nodes corresponding to action capabilities of the real world entities. Each of the participant-entity nodes and the action nodes is associated with properties, relationships, and relationship properties. Underlying the action graph layer is a standard graph layer that stores nodes, node properties associated with the nodes, edges, and edge properties associated with the edges, wherein the nodes correspond to the participant-entity nodes and the action nodes. Further, underlying the standard graph layer is a backend database layer that stores corresponding data and metadata.

Abstract: Knowledge representation in multi-layered database includes systems and methods for storing and retrieving data in the multi-layered database. In the multi-layered database, an action graph database includes participant-entity nodes corresponding to real world entities and action nodes corresponding to action capabilities of the real world entities. Each of the participant-entity nodes and the action nodes is associated with properties, relationships, and relationship properties. Underlying the action graph layer is a standard graph layer that stores nodes, node properties associated with the nodes, edges, and edge properties associated with the edges, wherein the nodes correspond to the participant-entity nodes and the action nodes. Further, underlying the standard graph layer is a backend database layer that stores corresponding data and metadata.

Abstract: Method(s) and system(s) providing for providing context based conversations are described here. The method may include receiving user data pertaining to a user. The user data includes registration information of the user and metadata associated with the user. The method may include determining a pre-defined role of the user based on the registration information. Further, the method may include providing restricted access to a users' data repository to the user, based on the role of the user. The method includes obtaining a text input pertaining to a conversation. Based on the text input an expression is generated. Further, one of a discussion service, a learning service, and an unlearning service is invoked, based on the expression and the metadata associated with the user. Based on at least one of the invoking services and the metadata associated with the user, retrieving a response. The response is shared with the user.

Abstract: A method for providing recommendations for customers is described. The method comprises obtaining transaction data associated with one or more products being purchased by a customer. The method further comprises generating a customer household graph, wherein the customer household graph comprises a customer household node associated with the customer, a product superset node, and one or more product nodes associated with the product superset node. Further, at least one product metadata node associated with each of the one or more product nodes is determined. Further, at least one user node is associated with the customer household node based on the at least one product metadata node. Further, a user group node associated with the customer household node is determined based on the at least one user node. Further, one or more recommendations to be provided to the user are ascertained.

Abstract: Knowledge representation in a multi-layered database includes systems and methods for storing and retrieving data in the multi-layered database. The multi-layered database includes an object database layer that stores objects corresponding to real world entities and each object is associated with object properties, object relationships, and relationship properties. Underlying the object database layer is a graph database layer that stores nodes, node properties associated with the nodes, edges, and edge properties associated with the edges, wherein the nodes correspond to objects, node properties are indicative of the object properties, the edges are indicative of the object relationships, and the edge properties are indicative of the relationship properties of the object. Further, underlying the graph database layer is a backend database layer that stores corresponding data and metadata. Data can be stored and retrieved from the multi-layered database by composing and decomposing information between layers.