Ig-hoon Lee

Building an operational product ontology system

A base of clearly defined product information is a key foundation for an e-commerce system. The manipulation and exchange of semantically enriched and precise product information can enhance the quality of an e-commerce system and offer a high level of interoperability with other systems. Product information consists of product attributes and the relationships between products. Product categorization (or classification) is one type of such relationships. Ontology can play an important role in the formalization of product information. Although the idea of utilizing ontology for e-Catalogs has been raised before, we are yet to find an operational implementation of applying ontology in the domain. In this paper, we report on our recent effort to build an operational product ontology system for a government procurement service. The system is designed to serve as a product ontology knowledge base; not only for the design and construction of product databases but also for search and discovery of products. Especially, the keyword-based searching over product ontology database demands different techniques from those over conventional document databases or relational databases, and should be designed to reflect particular characteristics of product ontology. We also introduce some other issues that we have experienced in the project, and those issues include product ontology modeling, ontology construction and maintenance, and visualization. Our work presented herein may serve as a reference model for similar projects in the future.

Practical issues for building a product ontology system

A base of clearly defined product information is a key foundation for an e-commerce system. The manipulation and exchange of semantically enriched and precise product information can enhance the quality of an e-commerce system and offer a high level of interoperability with other systems. Product information consists of product attributes and the relationships between products. Product categorization (or classification) is one type of such relationships. Ontology can play an important role in the formalization of product information. Although the idea of utilizing ontology for e-catalogs has been raised before, we are yet to find an operational implementation of applying ontology in the domain. In this paper, we report on our recent effort to build an operational product ontology system for the government procurement service. The system is designed to serve as a product ontology knowledge base; not only for the design and construction of product databases but also for search and discovery of products. We introduce some of the issues that we have experienced in the project, so that our work may serve as a reference model for similar projects in the future.

CST-trees: cache sensitive t-trees

Researchers have modified existing index structures into ones optimized for CPU cache performance in main memory database environments. A Cache Sensitive B+-Tree is one of them. It is designed to minimize the impact of cache misses for B+-Trees and it has been known to be more effective than other types of main memory index structure including T-Trees. In this paper, we introduce a Cache Sensitive T-Tree (CST-Tree) and show how T-Trees can also be redesigned to be cache sensitive. We present an experimental performance study which shows that our Cache Sensitive T-Trees can outperform the original T-Trees and Cache Sensitive B+-Trees on average 65 percent and 17 percent, respectively.

Making T-Trees Cache Conscious on Commodity Microprocessors

Recent research shows that the database performance can be significantly improved by the effective cache utilization of the conventional microprocessors. Researchers have modified existing index structures into ones optimized for CPU cache performance in main memory database environments. A Cache Sensitive B+-Tree is designed to minimize the impact of cache misses for B+-Trees and it has been known to be more effective than other types of main memory index structure including T-Trees. In this paper, we introduce a Cache Sensitive T-Tree (CST-Tree) and show how T-Trees can also be redesigned to be cache sensitive. We present an experimental performance study which shows that our Cache Sensitive T-Trees can outperform the original T-Trees and Cache Sensitive B+-Trees on commodity microprocessors.

A snappy b+-trees index reconstruction for main-memory storage systems

A main memory system employs a main memory rather than a disk as a primary storage and efficiently supports various real time applications that require high performance. The time to recover the system from failure needs to be shortened for real time service, and fast index reconstruction is an essential step for data recovery. In this paper, we present a snappy B+-Tree reconstruction algorithm called Max-PL. The basic Max-PL (called Max) stores the max keys of the leaf nodes at backup time and reconstructs the B+-Tree index structure using the pre-stored max keys at restoration time. Max-PL employs a parallelism to Max in order to improve the performance. We analyze the time complexity of the algorithm, and perform the experimental evaluation to compare its performance with others. Using Max-PL, we achieve a speedup of 2 over Batch Construction and 6.7 over B+-tree Insertion at least.

Cache conscious trees: how do they perform on contemporary commodity microprocessors?

Some index structures have been redesigned to minimize the cache misses and improve their CPU cache performances. The Cache Sensitive B+- Tree and recently developed Cache Sensitive T-Tree are the most well-known cache conscious index structures. Their performance evaluations, however, were made in single core CPU machines. Nowadays even the desktop computers are equipped with multi-core CPU processors. In this paper, we present an experimental performance study to show how cache conscious trees perform on different types of CPU processors that are available in the market these days.

An architecture for supporting batch query and online service in Very Large Database systems

The unprecedented growth of the telecommunications industry and exponential increase in real-time online transactions has created the need for a database (DB) system capable of managing massive amounts of data. However, current very large DB (VLDB) systems can become overwhelmed, and if, for example, a batch query is made while a transaction is being executed, the online service may become limited or system performance may decrease. We propose a partially distributed DB model to address this problem. The model partially separates a batch server, resulting in increased performances in transaction response time and throughput

Cache conscious trees on modern microprocessors

Recent research shows that database performance can be significantly improved by the effective cache utilization of conventional microprocessors. Researchers have modified existing index structures into ones optimized for CPU cache performance in main memory database environments. The Cache Sensitive B+-Tree and recently developed Cache Sensitive T-Tree are the most well-known cache conscious index structures. In this paper, we present an experimental performance study to show how cache conscious trees perform on different types of modern CPU processors. We perform experiment evaluation on basic tree operations, search, range search, and insertion/deletion operation.