Product Recommendation with Interactive Query Management and Twofold Similarity
نویسندگان
چکیده
This paper describes an approach to product recommendation that combines in a novel way contentand collaborative-based filtering techniques. The system helps the user to specify a query that filters out unwanted products in electronic catalogues (content-based). Moreover, if the query produces too many or no results, the system suggests useful query changes that save the gist of the original request. This process goes on iteratively till a reasonable number of products is selected. Then, the selected products are ranked exploiting a case base of recommendation sessions (collaborative-based). Among the user selected items the system ranks higher items that are similar to those selected by other users in similar sessions (twofold similarity). The approach has been applied to a web travel application and it has been evaluated with real users. The proposed approach: a) reduces dramatically the number of user queries, b) reduces the number of browsed products and c) the selected items are found first on the ranked list.
منابع مشابه
Discovering Popular Clicks\' Pattern of Teen Users for Query Recommendation
Search engines are still the most important gates for information search in internet. In this regard, providing the best response in the shortest time possible to the user's request is still desired. Normally, search engines are designed for adults and few policies have been employed considering teen users. Teen users are more biased in clicking the results list than are adult users. This leads...
متن کاملA Survey Report on the Novel Approach on Use of Recommendation Outline in Query Recommender System
The DBMS applications are becoming increasingly popular in the scientific community to support the interactive exploration of huge data. A result of heavy usage has also lead to a lot of tavles generated in the warehouse. This has tremendously increased the need for recommendation system & various tools for the user as user is not capable to explore such huge data by using Structured Query lang...
متن کاملPersonalized Product Recommendation through Interactive Query Management and Case-Based Reasoning
This position paper describes a novel approach to the design of personalized recommender systems. The approach integrates content-based and collaborative filtering techniques, case-based reasoning, and an HCI perspective to system evaluation and user modeling. Following this method, we developed and tested a system prototype that helps the user to construct a travel plan by recommending promisi...
متن کاملLetting Users Assist What to Watch: An Interactive Query-by-Example Movie Recommendation System
In this article we propose an interactive Web-based movie recommendation system namely MISRec employing object recognition for movie thumbnails. The proposed system carries out object recognition on movie thumbnails or DVD cover-photos in a real-time manner, and recommends movies based on user’s historical preferences and the query intention. Unlike typical preference-based recommendation syste...
متن کاملQuery-URL Bipartite Based Approach to Personalized Query Recommendation
Query recommendation is considered an effective assistant in enhancing keyword based queries in search engines and Web search software. Conventional approach to query recommendation has been focused on query-term based analysis over the user access logs. In this paper, we argue that utilizing the connectivity of a query-URL bipartite graph to recommend relevant queries can significantly improve...
متن کامل