Nobuyoshi Sato

Fresh Information Retrieval Using Cooperative Meta Search Engines

In web page retrievals, search engines are usually used. However, conventional search engines have a problem in that their update intervals are very longb ecause they are based on centralized architecture, which gathers documents using robots. So we proposed the Cooperative Search Engine (CSE) in order to reduce the update interval. CSE is a distributed search engine, which integrates small local search engines into a large global search engine by using local meta search engines. A local meta search engine hides a local search engine in each web site. Although CSE can reduce the update interval, the retrieval performance is not enough. So, we proposed several speed up techniques. In this paper, we describe the structure and behavior of CSE and its efficiency.

Persistent cache in Cooperative Search Engine

Cooperative Search Engine (CSE) is a distributed search engine, which can update indexes in a very short time for the purpose of fresh information retrieval. In CSE, the retrieval performance is dependent on cache contents because communication delay occurs at retrieval time. On the other hand, however, cache is invalidated as soon as indexes are updated. Therefore, we need persistent cache that can hold valid data before and after updating. In this paper we describe the principle and evaluations of persistent cache.

Temporal Ranking for Fresh Information Retrieval

In business, the retrieval of up-to-date, or fresh, information is very important. It is difficult for conventional search engines based on a centralized architecture to retrieve fresh information, because they take a long time to collect documents via Web robots. In contrast to a centralized architecture, a search engine based on a distributed architecture does not need to collect documents, because each site makes an index independently. As a result, distributed search engines can be used to retrieve fresh information. However, fast indexing alone is not enough to retrieve fresh information, as support for temporal information based retrieval is also required. In this paper, we describe temporal information retrieval in distributed search engines. In particular, we propose an implementation of temporal ranking.

Distributed information retrieval by using cooperative meta search engines

Information retrieval is frequently used for the Internet. However, we face the problem that the update intervals of conventional search engines are too long. It is difficult for conventional search engines to make their intervals short because they are based on a centralized architecture. So, we proposed the Cooperative Search Engine (CSE), which is based on a distributed architecture. CSE can realize the shortening of the update interval. In CSE, a large search engine is constructed from multiple local meta search engines that cooperate with each other. CSE can accomplish correct ranking in a distributed fashion because each local meta search engine hides the difference between its local search engine and the others. The article discusses the design and experimental evaluations of CSE.

Temporal information retrieval in cooperative search engine

In business, the retrieval of up-to-data, or fresh, information is very important. It is difficult for conventional search engines based on a centralized architecture to retrieve fresh information, because they take a long time to collect documents via Web robots. In contrast to a centralized architecture, a search engine based on a distributed architecture does not need to collect documents, because each site makes an index independently. As a result, distributed search engines can be used to retrieve fresh information. However, fast indexing alone is not enough to retrieve fresh information, as support fro temporal information based retrieval is also required. In this paper, we describe temporal information retrieval in distributed search engines. In particular, we propose a content-based comparison method to avoid spamming.

Initial Design of Distributed Identification System for Geographical Origin by Trace Element Analysis

In Japan, districts where agricultural products are cultivated have recently begun to make their locality into a brand. In order to take advantage of this brand creation, some retailer and distributor camouflage agricultural products cultivated in non-branded districts to be sold as the branded districts goods with its attendant higher brand values; thus fraudulently raising their own prices. In order to prevent camouflaging of products from non-branded districts, traceability systems that mark an ID on the packaging have been proposed. However, these traceability systems cannot prevent fraud within the systems themselves, such as the use of illegally acquired IDs. Therefore, we proposed a system that distinguishes the various places of cultivation of green groceries by analyzing trace elements, which means extremely small quantities of elements, in the cultivated products and then storing this information in distributed databases. In this paper, firstly we show that discrimination is possible by correlation analysis on the results of our trace elements analysis, and we describe the outline and design of a system which identifies cultivated places of green groceries

A distributed search engine for fresh information retrieval

In information retrieval of web pages, we usually use search engines. A conventional search engine has the problem that the update interval is very long because it is based on centralized architecture, which collects documents by using robots. So, we have developed a distributed search engine, cooperative search engine (CSE) in order to reduce the update interval. In CSE, a global search engine is constructed with multiple meta search engines, which hide each local search engine in each Web site. CSE can make the update interval very short by indexing on each web site. In this paper we describe the framework of CSE and its efficiency.

Target selection by similarity preserve hash in distributed system for geographical origin identification of vegetables

Recently, camouflaging geographical origin of agricultural products is a major problem in Japan. Now we are developing a distributed system which identifies geographical origin of vegetables by analyzing, accumulating and comparing trace element compositions of vegetables. This system stores compositions of trace, or very small quantities of elements into database which located on farming districts, and compares them to trace element compositions of vegetables which gathered from distribution channel such as markets, food factories. Objective of this system is verifying geographical origin information by food traceability system and deter camouflaging geographical origin. However, in this system, all sites in farming districts must be searched to identify geographical origin. In this paper, we describe a method to reduce the number of targets to identify geographical origin using similarity preserve hash (SPH).

FTF-IDF scoring for fresh information retrieval

For most businesses, fresh information retrieval is very important. However, it is difficult for conventional search engines based on centralized architecture to retrieve really fresh information, because they take a long time to collect documents via Web robots. In contrast to a centralized architecture, a search engine based on a distributed architecture does not need to collect documents, because each site independently makes an index. As this result, distributed search engines can retrieve really fresh information. However, fast indexing is not enough to easily retrieve fresh information. The value of information is determined by both freshness and relevance. Traditional ranking methods consider either freshness or relevance; so, we proposed FTFIDF (fresh term frequency multiplied by inverse document frequency) as a scoring method that considers both freshness and relevance.

Information retrieval based on temporal attributes in WWW archives

Today, WWW is a media needed for us. Therefore, WWW should be archived and it should be also allowed to retrieve anytime. In such a digital archive, temporal information retrieval is very important. Temporal information retrieval is a kind of information retrieval based on temporal attributes of a document. In order to realize temporal information retrieval, we need the huge storage in which all of documents from past to future are stored. This is very difficult for a conventional centralized system. But, it is possible for a distributed system. In this paper, we propose temporal information retrieval based on distributed search engine.