Shinkaku Kashiji

An efficient e-mail filtering using time priority measurement

Although E-mail systems are one of the most useful communication tools for business, education, etc., missing important E-mail messages become a very serious problem. It is very useful filtering supports for users to pick up important messages or to neglect unnecessary messages. This paper presents a method of determining the time priority for E-mail messages. Multi-attribute rules are defined to detect complex time expressions and a set pattern-matching machine is proposed. It enables us to protect missing messages with important time information because the presented method can classify and rank them according to time priority measurement automatically. From the simulation results of determining time priority, the presented pattern-matching method is about 4 times faster than the traditional string pattern-matching method. From the results of filtering 5172 sentences, it is verified that precision and recall of the presented method becomes 95% and 96%, respectively. From the experimental results of determining 10 highest messages among 100 E-mail, it is verified that filtering time by the proposed measurement is from 9.7 to 16.6 faster than a non-filtering method.

A new compression method of double array for compact dictionaries

Speed and storage capacity are very important issues in information retrieval system. In natural language analysis, double array is a well-known data structure to implement the trie, which is a widely used approach to retrieve strings in a dictionary. Moreover, double array helps for fast access in a matrix table with compactness of a list form. In order to realize quite compact structure for information retrieval, this paper presents a compression method by dividing the trie constructed into several pieces (pages). This compression method enables us to reduce the number of bits representing entries of the double array. The obtained trie must trace to the pages that cause slow retrieval time, because of a state connection. To solve this problem, this paper proposes a new trie construction method to compress and minimize the number of state connections. Experimental results applying for a large set of keys show that the storage capacity has been reduced to 50%. Moreover, our new approach has the same retrieval speed as the old one.

Intelligent QA Systems Using Semantic Expressions

In the man-machine interfaces, it is important to use dialogue understanding technologies. One of the practical application fields is a question and answering (QA) systems. In order to reply appropriate answers for users questions, this paper presents a dialogue technique by transforming semantic expressions for both requests and answers. The measurements for the disrepute of the QA system are introduced for requests and answers, respectively. For the KAMOKUMA QA system generating answers which are reflecting users intension, the presented scheme is applied. For the AQ data with 7,518 requests, the real time simulation to estimate users sufficiency is computed.

An new E-mail filtering technique using time priority measurement

Although E-mail systems are one of the most useful communication tools for business, education, etc., missing important E-mail messages becomes very serious problems. It is very useful filtering supports for users to pick up important messages or to neglect unnecessary messages. This work presents a method of determining the time priority for E-mail messages. Multiattribute rules are defined to detect complex time expressions and a set pattern-matching machine is proposed. It enables us to protect missing messages with important time information because the presented method can classify and rank them according to time priority measurement automatically. From the simulation results of determining time priority, it turned out that the presented pattern-matching method is from about 4 times faster than the traditional string pattern-matching method. From the results of filtering 5,172 sentences, it is verified that precision and recall of the presented method becomes 95% and 96%, respectively. From the experimental results of determining 10 highest messages among 100 E-mail, it is verified that filtering time by the proposed measurement is from 9.7 to 16.6 faster than that of a nonfiltering method.

An improvement key deletion method for double-array structure using single-nodes

A trie is a well known method for various dictionaries, such as spelling check and morphological analysis. A double-array structure is an efficient data structure combining fast access of a matrix form with the compactness of a list form. The drawback of the double-array is that the space efficiency degrades by empty elements produced in key deletion. Morita presented a key deletion method eliminating empty elements. However, the space efficiency of this method is low for high frequent deletion and deletion takes much time because the cost depends on the number of the empty elements. This paper presents a fast and compact deletion method by using the property of nodes that have no brothers. From simulation results for 100,000 keys, the present method is about 330 times faster than Moritas method and keeps high space efficiency.

A Fast Dynamic Method Using Memory Management

Full-text search is widely used for various services of the Internet. A more high-speed and a more efficient full-text search technology are necessary because of the amount of increasing handled document and corresponding document data every day. This paper proposes an adaptive block management algorithm that is efficient for dynamic data management method. This algorithm is applied for inverted file searching. The new method is speeding up character string retrieval by first making the full-text search of Uni-gram and by the full-text search of Bi-gram. This paper proposes a method of enhancing the static full-text search system of Bi-gram to the dynamic full-text search system of Bi-gram. Moreover, this paper presents an efficient achievement method of the dynamic full-text search system of Bi-gram using effectiveness of the adaptive block management structure.

A Method of Extracting and Evaluating Popularity and Unpopularity for Natural Language Expressions

Although a user’s opinion, or a live voice, is very useful information for text mining of the business, it is difficult to extract popularity and unpopularity impressions of users from texts written in natural language. The popularity and unpopularity impressions discussed here depend on user’s claims, interests and demands. This paper presents a method of determining these impressions in commodity review sentences. Multi-attribute rule is introduced to extract the impressions from sentences, and four-stage-rules are defined in order to evaluate popularity and unpopularity impressions step by step. A deterministic multi-attribute pattern matching algorithm is utilized to determine the impressions efficiently. From simulation results for 2,240 review comments, it is verified that the multi-attribute pattern matching algorithm is 44.5 times faster than the Aho and Corasick method. The precision and recall of extracted impressions for each commodity are 94% and 93%. Moreover, the precision and recall of the resulting impressions for each rule are 95% and 95%, respectively.

A New Method of Detecting Time Expressions for E-mail Messages

Although E-mail systems are one of the most useful communication tools for business, education, etc,. It is very useful filtering supports for users to pick up important messages or to neglect unnecessary messages. This paper presents a method of determining the time priority for E-mail messages. Multi-attribute rules are defined to detect complex time expressions and a set pattern-matching machine is proposed. It enables us to protect missing messages with important time information because the presented method can classify and rank them according to time priority measurement automatically. From the simulation results of determining time priority, the presented pattern-matching method is from about 4 times faster than the traditional string pattern-matching method. From the results of filtering 5,172 sentences, precision and recall of the presented method becomes 95% and 96%, respectively. From the experimental results of determining 10 highest messages among 100 E-mail, filtering time is from 9.7 to 16.6 faster than that of a non-filtering method.

A high-speed dynamic full-text search method by using memory management

Full-text search is widely used for various services of the Internet. A more high-speed and a more efficient full-text search technology is necessary because of the amount of increasing handled document and corresponding document data every day. This paper proposes an adaptive block management algorithm that is efficient for dynamic data management method. This algorithm is applied for inverted file searching. The new method speeds up character string retrieval by first making a full-text search of uni-gram and a full-text search of bi-gram. This paper proposes a method for enhancing the static full-text search system of bi-gram to the dynamic full-text search system of bi-gram. Moreover, this paper presents an efficient achievement method of the dynamic full-text search system of bi-gram using effectiveness of the adaptive block management structure.