The document proposes an approach to efficiently find the top K target objects that are related to and best match a set of keywords, by exploiting relationships between documents and objects. It presents a system that indexes documents and relationships, defines scoring functions to aggregate relevance scores from related documents, and employs an early termination strategy using upper and lower bounds to avoid computing scores for all objects.

1. Ranking Objects by Exploiting Relationships: Computing Top-K over Aggregation Kaushik Chakrabarti, Venkatesh Ganti, Jiawei Han, Dong Xin, Microsoft Research, University of Illinois SIGMOD 2006 Reporter: Chieh-Chang Yang Date: 2007/05/15

6. Introduction

10. System Overview

16. SQL Implementation

21. Candidate Generation

27. Candidate Generation

33. Experiment

34. Experiment