Towards More Effective Solution Retrieval in IT Support Services Using Systems Log

Abstract

Technical support agents working in the IT support services field resolve IT problems. They are often faced with the daunting task of identifying the correct solution document through a search system from large corpora of IT support documents. Based on the observation that system logs may contain critical information for identifying the root cause of IT problems, we explore the idea of automatic query expansion by using system logs as a bridge to link queries with the most relevant documents. Given the original query from a user such as a technical support agent, an intermediate query is first formed by adding key terms extracted from system logs using domain-specific rules. Based on topic models, further key terms are selected from corpora of IT support documents, which are combined with the intermediate query to form the final query. Our experimental results show that expanding queries using system logs together with topic models yields better performance in retrieving relevant IT support documents than using topic models only.