With information technologies being increasingly involved in areas such as (online) shopping, entertainment or advertisement, computer systems are bound to be able to process Kansei information, i.e. information relevant to users' sensibilities. Rather than modeling the biology of users' sensibilities, we suggest a functional approach by modelling the translation process between different modalities of expression of a same Kansei concept. We hypothesizethat this translation process can be grounded into the categorization of users's perception, i.e. the extraction of structures in the multimedia information. Because this translation process is intrisincally variable, we propose a computational agent, called K-Agent, able to learn categories in its visual perception and interactively evolve a translation language. The K-Agent consists of three main modules: a multi-features image processing unit, a learning kernel that iteratively constructs the translation language, and a feedback interpreter system which incorporates self-supervision and user feedback to structurally tune the learning kernel. The concept of K-Agent has been evaluated in a real-world application involving user Kansei, more specifically, the filtering of images against a given user Kansei impression. Our experimental results demonstrate the feasibility of the concept as well as a superior performance compared to manually filtering the output of existing search engines.

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We propose an effective method for resolving overlapping ambiguities found in sentential analyses of Chinese. It detects the ambiguities by a FBMM scanner, resolves them by using the relevancy value (RV), a statistical measure for word co-occurrences taken from textual data on the Internet, and selects the correct word sequence for the sentence being analyzed. We use contextual information also when RVs are considered not sufficient to resolving the ambiguities and choosing the correct word sequence. An experiment for selecting the desired sequences shows a success rate of about 85%. This result is convincing and far better than those in other comparable studies.

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Given a question and a set of its candidate answers, the task of answer validation (AV) aims to return a Boolean value indicating whether a given candidate answer is the correct answer to the question. Unlike previous works, this paper presents an unsupervised model, called the U-model, for AV. This approach regards AV as a classification task and investigates how effectively using redundancy of the Web into the proposed architecture. Experimental results with TREC factoid test sets and Chinese test sets indicate that the proposed U-model with redundancy information is very effective for AV. For example, the top@1/mrr@5 scores on the TREC05, and 06 tracks are 40.1/51.5% and 35.8/47.3%, respectively. Furthermore, a cross-model comparison experiment demonstrates that the U-model is the best among the redundancy-based models considered. Even compared with a syntax-based approach, a supervised machine learning approach and a pattern-based approach, the U-model performs much better.

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We propose a query transitive translation system of a CLIR (Cross Language Information Retrieval) for a source language with a poor data resource. Our research aim is to do the transitive translation with a minimum data resource of the source language (Indonesian) and exploit the data resource of the target language (Japanese). We did two kinds of translation, a pure transitive translation and a combination of direct and transitive translations. In the transitive translation, English is used as the pivot language. The translation consists of two main steps. The first is a keyword translation process which attempts to make a translation based on available resources. The keyword translation process involves many target language resources such as the Japanese proper name dictionary and English-Japanese (pivot-target language) bilingual dictionary. The second step is a process to select some of the best available translations. We combined the mutual information score (computed from target language corpus) and TF × IDF score in order to select the best translation. The result on NTCIR 3 (NII-NACSIS Test Collection for IR Systems) Web Retrieval Task showed that the translation method achieved a higher IR score than the machine translation (using Kataku (Indonesian-English) and Babelfish/Excite (English-Japanese) engines). The transitive translation achieved about 38% of the monolingual retrieval, and the combination of direct and transitive translation achieved about 49% of the monolingual retrieval which is comparable to the English-Japanese IR task.

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次世代のメディアのデザインを考えた場合, コンテンツ自体の魅力とコンテンツとユーザのインタラクションが重要な課題になるであろう。ユーザは画面に表示されたメニューを選択して情報機器を使用するが, ユーザがある情報の提示を期待して機器を操作したときに, 機器がユーザの期待したコンテンツを表示されなければインタラクションのストレスは大きなものとなる。本研究では情報ニーズとコンテンツデザインの関わりについて学生を対象として実施した生活情報化ニーズのアンケート調査結果を分析した。公共情報機器は設置される場所によっ情報ニーズが異なるとした仮説のもとに, 情報ニーズ項目と公共情報端末の設置ニーズを分析した結果, 今後の研究の予備的な結論として, 公共情報機器を使用する不特定多数ユーザの情報ニーズを考える場合, 情報機器の設置場所はユーザの利用目的のフィルターの役割を果たすことができ, 設置場所に応じた情報サービスの提供がユーザのニーズにコンテンツを対応させることにおいて有効であると考えられる。

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As the internet becomes the basic resource of information, not only texts but images retrieval systems have been appeared. However, many of those supply only a list of images, so we have to seek the expecting images one by one. Although, image labeling is one of the solutions of such a problem, various words are labeled to an image if the words are extracted from only one Web page. Therefore, this paper proposes an image clustering system that labels images by words related to a search keyword. This relationships are measured by Web pages in WWW. By the experimental results, users were enabled to find the intended images more faster than the ordinal image search system.

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The fast evolving information space forms a new arena for geographical analysis which enhances our understanding of the structure of digital spaces, thus potentially affecting the urban lives and socio-economic activities that have become increasingly dependent on information technology. Assuming that the information space forms a quantitatively measurable entity and should be addressed in the geographical context, this study combines spatial analysis techniques with GIS technologies to explore the structure of the World Wide Web in terms of its node connectivity. We investigate the number of homepages and the reciprocal hyperlinks between 180 global Internet domains and determine the location that is central to the information space. The hyperlink structure is treated as a network and a virtual distance between these domains is calculated from which the mini-sum distance of all the sites is determined. The results are overlaid onto an atlas to help to understand the relationship between the information space and the existing geographical space.

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インタ-ネットの発達により環境情報のディジタル化が急速に進む中で, GISを含む造園デ-夕のディジタル化がどのような現状にあるか調べると共に, GISの入力作業における問題点を明らかにする事を目的として, WWWにおいてホームペ-ジの現況を把握するとともに, 実際にGISの入力を行うこととした。 その結果,(1) インターネットは確実に造園の分野にも浸透しつつあるが日本はまだ後進国である,(2) 最もGISの応用に力を入れていると思われる造園の部門でも全体の10%にも満たない,(3) アナログからディジタルへの移行は長いアナログの慣習が要因となって容易には進まない, という3点が明らかとなった。

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In this paper, we propose an improved SO-PMI (Semantic Orientation Using Pointwise Mutual Information) algorithm, for use in Japanese Weblog Opinion Mining. SO-PMI is an unsupervised approach proposed by Turney that has been shown to work well for English. When this algorithm was translated into Japanese naively, most phrases, whether positive or negative in meaning, received a negative SO. For dealing with this slanting phenomenon, we propose three improvements: to expand the reference words to sets of words, to introduce a balancing factor and to detect neutral expressions. In our experiments, the proposed improvements obtained a well-balanced result: both positive and negative accuracy exceeded 62%, when evaluated on 1,200 opinion sentences sampled from three different domains (reviews of Electronic Products, Cars and Travels from Kakaku. com). In a comparative experiment on the same corpus, a supervised approach (SA-Demo) achieved a very similar accuracy to our method. This shows that our proposed approach effectively adapted SO-PMI for Japanese, and it also shows the generality of SO-PMI.

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This paper proposes a method for discovering Web communities. A complete bipartite graph K_{i, j} of Web pages can be regarded as a community sharing a common interest. Discovery of such community is expected to assist users’ information retrieval from the Web. The method proposed in this paper is based on the assumption that hyperlinks to related Web pages often co-occur. Relations of Web pages are detected by the co-occurrence of hyperlinks on the pages which are acquired from a search engine by backlink search. In order to find a new member of a Web community, all the hyperlinks contained in the acquired pages are extracted. A page which is pointed by the most frequent hyperlinks is regarded as a new member of the community. We have build a system which discovers complete bipartite graphs based on the method. Only from a few URLs of initial community members, the system succeeds in discovering several genres of Web communities without analyzing the contents of Web pages.

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The role of the Internet has become more and more important for both educators and students of English to obtain useful information quickly and easily. With the help of various search engines, one can find required information relatively easily. However, one may wonder which search engine should be used. The purpose of this paper is to examine which search engine is recommended to conduct searches on the Internet. A query is selected, single keyword searches and Implied Boolean searches were conducted, and retrieval matches, accuracy, access time, and ease-of use of seven search engines were compared. As a result, Alta Vista search engine indicated the largest number of hits in three single keyword searches, the second largest number of hits in the Implied Boolean search, and the largest relevancy rate (100%) in the Implied Boolean search. According to the result, Alta Vista is the best search engine among Web-based search engines. Also, Alta Vista was compared with the DIALOG, one of charged online search services. According to the comparison result, Alta Vista still needs to be improved in terms of proximity operators and truncation operators.

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Recent Trends in Homepages of Occupational Health Journals on the Internet: Yuki KAMIBEPPU, et al. Department of Public and Occupational Health Nursing, School of Health Sciences, University of Occupational and Environmental Health—The usefulness of homepages (HP) of twelve occupational health journals including the Journal of Occupational Health was assessed by using the HP of the British Medical Journal as the “gold standard”. There was a wide range of available information and functions for the HP of the ten occupational health journals with URL addresses. Basic information such as instruction to authors and table of contents was provided in most journals, but few journals provided innovative functions such as access to full texts. There is room for improvement in HPs of most occupational health journals to serve as a convenient tool and source of information for the relevant professionals.

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