305,366 research outputs found
Identification Of Diseases In Rice Plant Using Chatbot With Methode Artificial Intelligence Markup Language and Normalization
No full textInformation Services in agriculture are entering the era of industrial revolution 4.0, always associated with the use of automation machines integrated with the internet network. The technological sophistication of this era makes many conditions change. The chatbot application is one of the right solutions to solve farmer problems, this farmer chatbot application is about the information on handling rice plants, and this application uses the Artificial Intelligence Markup (AIML) method. The purpose of this study was to test the accuracy of the answers to the chatbot. This research method uses question data with words under 5 words and above 5 words, and uses question data according to keywords and outside keywords in this chatbot, with 50 question data, with each question data tested four times than taken the average. average. The results of this study are to get an accuracy of 90.9%, while the response time for answering questions of less than 5 words is 0.01 seconds, and for more than 5 words is 0.02 seconds with a data set of 1000 lines
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
Market Potential Research For The Revitalization Of Traditional Markets
No full textRevitalization of traditional markets is one of the programs announced by the government primarily to encourage small and medium businesses can grow. PD Pasar Surya is a traditional market managers in Surabaya, which manages 81 traditional markets and only 20% are already revitalized, but during this process of revitalization is based only on observation and intuition, unsupported by the survey results and analysis of market potential. For that reason this study examines how the potential of traditional markets in the east branch, north branch and south branch so that it can be seen how consumer preferences and segmentation in an effort to obtain data on potential markets. Statistical analysis used was cluster analysis to see the segmentation of consumers based on preferences. The way to get the data in this study is to find secondary data and primary data in BPS by a survey carried out for two months. This research result is expected to be used in policymaking by PD Pasar Surya in determining the traditional markets which are worth to be revitalized and this result will be use to make Decission Support System for next program.
Keywords : component Market Potensial Research, Traditional Market, Revitalization, Cluster Anaysis
Mining e-mail content for author identification forensics
No full textWe describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different email topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation
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