Abstract: Described are systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. A system and method may facilitate determining user and community member activity in the virtual storefront based on which weighted keywords are derived. A topic set containing various weighted keywords may be iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources. A server may be configured for refining the topic set by modifying a baseline session keyword weight or a baseline contextual keyword weight based on a total topic set weight, an elasticity parameter, core topic keyword weights associated with core topic keywords, session keyword weights, and/or contextual keyword weights; and identifying, based at least on the configured topic set, products to be presented to a user as product recommendations in the virtual storefront.

Abstract: Methods and Systems for displaying product recommendations at a virtual storefront by receiving product recommendations from a plurality of heterogeneous sources. The source servers send the product recommendations from their end that are then normalized and refined by a recommendation engine based on a plurality of factors ensuring that the products are presentable and sellable on the storefront. The recommendation collation is accomplished using a pipeline of stateless processors, thereby providing a highly scalable platform perfectly suited for cloud-based computational platforms.

Abstract: Described are systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. A system and method may facilitate determining user and community member activity in the virtual storefront based on which weighted keywords are derived. A topic set containing various weighted keywords may be iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources. A server may be configured for refining the topic set by modifying a baseline session keyword weight or a baseline contextual keyword weight based on a total topic set weight, an elasticity parameter, core topic keyword weights associated with core topic keywords, session keyword weights, and/or contextual keyword weights; and identifying, based at least on the configured topic set, products to be presented to a user as product recommendations in the virtual storefront.

Abstract: Methods and Systems for displaying product recommendations at a virtual storefront by receiving product recommendations from a plurality of heterogeneous sources. The source servers send the product recommendations from their end that are then normalized and refined by a recommendation engine based on a plurality of factors ensuring that the products are presentable and sellable on the storefront. The recommendation collation is accomplished using a pipeline of stateless processors, thereby providing a highly scalable platform perfectly suited for cloud-based computational platforms.

Abstract: Systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. The systems and methods facilitate continuous monitoring of user activity and community member activity in the topic-based virtual storefront based on which one or more weighted keywords are derived. A topic set containing various weighted keywords is iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources.

Abstract: Methods and Systems for displaying product recommendations at a virtual storefront by receiving product recommendations from a plurality of heterogeneous sources. The source servers send the product recommendations from their end that are then normalized and refined by a recommendation engine based on a plurality of factors ensuring that the products are presentable and sellable on the storefront. The recommendation collation is accomplished using a pipeline of stateless processors, thereby providing a highly scalable platform perfectly suited for cloud-based computational platforms.

Abstract: Methods and Systems for displaying product recommendations at a virtual storefront by receiving product recommendations from a plurality of heterogeneous sources. The source servers send the product recommendations from their end that are then normalized and refined by a recommendation engine based on a plurality of factors ensuring that the products are presentable and sellable on the storefront. The recommendation collation is accomplished using a pipeline of stateless processors, thereby providing a highly scalable platform perfectly suited for cloud-based computational platforms.

Abstract: Systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. The systems and methods facilitate continuous monitoring of user activity and community member activity in the topic-based virtual storefront based on which one or more weighted keywords are derived. A topic set containing various weighted keywords is iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources.

Abstract: Methods and Systems for displaying product recommendations at a virtual storefront by receiving product recommendations from a plurality of heterogeneous sources. The source servers send the product recommendations from their end that are then normalized and refined by a recommendation engine based on a plurality of factors ensuring that the products are presentable and sellable on the storefront. The recommendation collation is accomplished using a pipeline of stateless processors, thereby providing a highly scalable platform perfectly suited for cloud-based computational platforms.

Abstract: Systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. The systems and methods facilitate continuous monitoring of user activity and community member activity in the topic-based virtual storefront based on which one or more weighted keywords are derived. A topic set containing various weighted keywords is iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources.

Abstract: Methods and systems for extracting and displaying one or more products on a virtual storefront embedded in a topical community web page are disclosed. The displayed products may then be purchased by a user or a community member or a member of the group or forum directly at the virtual storefront. The community web page is related to a particular interest or a context and hosts information or media related to that particular context. The systems and methods disclosed herein may facilitate the community web page administrator, community web page owner, or any other person in similar capacity to either select one or more products statically or the products are dynamically extracted from one or more of a connected storefront or a marketplace or both.

Abstract: Methods and Systems for displaying product recommendations at a virtual storefront by receiving product recommendations from a plurality of heterogeneous sources. The source servers send the product recommendations from their end that are then normalized and refined by a recommendation engine based on a plurality of factors ensuring that the products are presentable and sellable on the storefront. The recommendation collation is accomplished using a pipeline of stateless processors, thereby providing a highly scalable platform perfectly suited for cloud-based computational platforms.

Abstract: Methods and systems for extracting and displaying one or more products on a virtual storefront embedded in a topical community web page are disclosed. The displayed products may then be purchased by a user or a community member or a member of the group or forum directly at the virtual storefront. The community web page is related to a particular interest or a context and hosts information or media related to that particular context. The systems and methods disclosed herein may facilitate the community web page administrator, community web page owner, or any other person in similar capacity to either select one or more products statically or the products are dynamically extracted from one or more of a connected storefront or a marketplace or both.

Abstract: Systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. The systems and methods facilitate continuous monitoring of user activity and community member activity in the topic-based virtual storefront based on which one or more weighted keywords are derived. A topic set containing various weighted keywords is iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources.