Multi-dimensional query expansion employing semantics and usage statistics
Embodiments relate to systems and methods employing personalized query expansion to suggest measures and dimensions allowing iterative building of consistent queries over a data warehouse. Embodiments may leverage one or more of: semantics defined in multi-dimensional domain models, user profiles defining preferences, and collaborative usage statistics derived from existing repositories of Business Intelligence (BI) documents (e.g. dashboards, reports). Embodiments may utilize a collaborative co-occurrence value derived from profiles of users or social network information of a user.
1. A computer-implemented method comprising:
providing a query expansion system comprising an engine, in communication with a user profile and with a business intelligence platform comprising a data warehouse, a multi-dimensional domain model, and a repository of documents;
causing the query expansion system to receive a query posed by a user to the business intelligence platform, the query comprising a measure of the multi-dimensional domain model;
causing the engine to determine a co-occurrence value for the query in the data warehouse based upon the repository of documents and a preference in the user profile, wherein determining the co-occurrence value comprises causing a second engine of the query expansion system to receive social/trust network information taking into account a relationship of the user to another entity in a social/trust network from the user profile to determine a collaborative co-occurrence value, wherein determining the collaborative co-occurrence value comprises applying a weight based upon a distance of the another entity from the user in the social/trust network information, wherein the social/trust network information comprises information from an enterprise directory; and
causing the query expansion system to display to the user a query result based upon the collaborative co-occurrence value.
2. The method of claim 1 wherein:
the query result is presented to the user as a first link to a first dimension of the multi-dimensional domain model, together with a second link to a second query result based upon a second dimension of the multi-dimensional domain model; and
the user accesses the query result comprising a chart, by activating the first link.
3. The method of claim 1 wherein determining the co-occurrence value comprises defining a Jaccard index.
4. The method of claim 1 wherein the social/trust network information comprises information from a social network.
5. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising:
providing a query expansion system comprising an engine, in communication with a user profile and with a business intelligence platform comprising a data warehouse, a multi-dimensional domain model, and a repository of documents;
causing the query expansion system to receive a query posed by a user to the business intelligence platform, the query comprising a measure of the multi-dimensional domain model;
causing the engine to determine a co-occurrence value for the query in the data warehouse based upon the repository of documents and a preference in the user profile;
wherein determining the co-occurrence value comprises causing a second engine of the query expansion system to receive social/trust network information taking into account a relationship of the user to another entity in a social/trust network from the user profile to determine a collaborative co-occurrence value, wherein determining the collaborative co-occurrence value comprises applying a weight based upon a distance of the another entity from the user in the social/trust network information, wherein the social/trust network information comprises information from an enterprise directory; and
causing the query expansion system to display to the user a query result based upon the collaborative co-occurrence value.
6. The non-transitory computer readable storage medium of claim 5 wherein:
the query result is presented to the user as a first link to a first dimension of the multidimensional domain model, together with a second link to a second query result based upon a second dimension of the multi-dimensional domain model; and
the user accesses the query result comprising a chart, by activating the first link.
7. The non-transitory computer readable storage medium of claim 5 wherein determining the co-occurrence value comprises defining a Jaccard index.
8. The non-transitory computer readable storage medium of claim 5 wherein the social/trust network information comprises information from a social network.
9. A computer system comprising:
one or more processors;
a software program, executable on said computer system, the software program configured to:
communicate with a query expansion system comprising an engine, in communication with a user profile and with a business intelligence platform comprising a data warehouse, a multi-dimensional domain model, and a repository of documents;
causing the query expansion system to receive a query posed by a user to the business intelligence platform, the query comprising a measure of the multi-dimensional domain model;
causing the engine to determine a co-occurrence value for the query in the data warehouse based upon the repository of documents and a preference in the user profile;
wherein determining the co-occurrence value comprises causing a second engine of the query expansion system to receive social/trust network information taking into account a relationship of the user to another entity in a social/trust network from the user profile to determine a collaborative co-occurrence value, wherein determining the collaborative co-occurrence value comprises applying a weight based upon a distance of the another entity from the user in the social/trust network information, wherein the social/trust network information comprises information from an enterprise directory; and
causing the query expansion system to display to the user a query result based upon the collaborative co-occurrence value.
10. The computer system of claim 9 wherein:
the query result is presented to the user as a first link to a first dimension of the multidimensional domain model, together with a second link to a second query result based upon a second dimension of the multi-dimensional domain model; and
the user accesses the query result comprising a chart, by activating the first link.
11. The computer system of claim 9 wherein determining the co-occurrence value comprises defining a Jaccard index.
12. The computer system of claim 9 wherein the social/trust network information comprises information from a social network.