The layer-seeds term clustering method: Enabling proactive situation-aware product recommendations in e-commerce dialogues

In e-commerce it is often crucial to provide customers a large choice of relevant offers. Users, however, seldom provides complete and comprehensive descriptions of their desires, therefore user interfaces are needed that can generate automatically expanded queries to the product database and proactively enrich the ongoing dialogue with recommendations of suitable products. Automatic query expansion is mostly based on thesaurus and/or user profiles. In e-commerce applications, specific thesauri reflecting the webstore's product categories are desirable. This work describes a method for the automatic construction of a thesaurus based on existing categories of documents. A clustering algorithm, the "Layer-Seeds method", is introduced, which facilitates the automatic generation of thesaurus reflecting the specific vocabulary occurring in a given collection of documents. The clustering works on terms extracted from the documents in a certain category and organizes them in a tree-like hierarchical structure-a thesaurus. The thesaurus is then employed for automatic query expansion in an e-commerce application in order to obtain better results for product searching. Experiments yield evidence that a significant increase of user satisfaction is achieved.