H. Ketmaneechairat, Chutima Kongketwanich, Thitinun Naijit
{"title":"Recommender system for Thai food cooking on smartphone","authors":"H. Ketmaneechairat, Chutima Kongketwanich, Thitinun Naijit","doi":"10.1109/ICDIM.2017.8244696","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244696","url":null,"abstract":"The purpose of this research were to develop the recommender system for Thai food cooking on smartphone and evaluate user's satisfaction on the recommender system for Thai food cooking on smartphone. This application has been developed to give users about Thai food cooking information. The application function is offline mode and can be displayed in two languages: Thai language and English language. This paper presents the design and implementation by using Android Software Development Kit. The results show that the users can search cooking method from category, cooking method, food name and ingredient. The application can show the detail of food as such as food name, picture of the food, ingredient and cooking method. The proposed application is better support for users that the users are used android mobile.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"397 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116331138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
André Petermann, G. Micale, Giacomo Bergami, A. Pulvirenti, E. Rahm
{"title":"Mining and ranking of generalized multi-dimensional frequent subgraphs","authors":"André Petermann, G. Micale, Giacomo Bergami, A. Pulvirenti, E. Rahm","doi":"10.1109/ICDIM.2017.8244685","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244685","url":null,"abstract":"Frequent pattern mining is an important research field and can be applied to different labeled data structures ranging from itemsets to graphs. There are scenarios where a label can be assigned to a taxonomy and generalized patterns can be mined by replacing labels by their ancestors. In this work, we propose a novel approach to generalized frequent subgraph mining. In contrast to existing work, our approach considers new requirements from use cases beyond molecular databases. In particular, we support directed multigraphs as well as multiple taxonomies to deal with the different semantic meaning of vertices. Since results of generalized frequent subgraph mining can be very large, we use a fast analytical method of p-value estimation to rank results by significance. We propose two extensions of the popular gSpan algorithm that mine frequent subgraphs across all taxonomy levels. We compare both algorithms in an experimental evaluation based on a database of business process executions represented by graphs.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115023753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring uncertainty to identify missing customer information relevant to the design process","authors":"Anna Marti Bigorra","doi":"10.1109/ICDIM.2017.8244651","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244651","url":null,"abstract":"The advances in customer information gathering techniques are constantly increasing. However, the tools used today to translate such information into product specifications provide lack of emphasis on communicating insights to engineering teams. In addition, little investigation on how the gathered customer information is helpful to product designers is rarely explored in the literature. At the end, this situation results in a still uncertain target setting process that increases the risk to set wrong product specifications due to the lack of customer information insightful to the designers. In order to quantify such, todays' risk assessment methodologies cannot be used. The reason is that they use a set of undesirable events as a starting point without ensuring that all possible undesirable events are considered. Thus, uncertainty cannot be estimated without knowing what customer information is relevant to designers. By means of the p-diagram and Analytical Hierarchy Process this paper proposes a novel way to identify what customer information is relevant to the design process and calculates uncertainty as the risk of designers' decisions to deviate from the customer picture due to the lack of relevant customer information. To do so, existing customer information from the company database is taken as basis. To show the validity of the proposed methodology, a case study regarding the balancing of electric consumption of an electric vehicle is proposed. Results show that the risk indicator helps the team members to identify what customer information is uncertain and therefore relevant to the design process as well as to establish a more customer-focused and context-specific information gathering strategy.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121875313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scientific visualizer in personal information management","authors":"G. Osinski, Veslava Osinska, Brian Camacho","doi":"10.1109/ICDIM.2017.8244674","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244674","url":null,"abstract":"Science maps can be used for comprehensive study of scientific research on different levels of organization: micro, meso and macro. All approaches need a distinct aggregation degree of analysis units. The structures of community or knowledge on local (meso) and global (macro) levels can be discovered due to bibliographic data processing and further visualization. There is a wide range of examples of these visualizations and their design. Although micro, an individual level is rather rarely considered by professionals and described in papers. The authors have demonstrated a web application — Scientific Visualizers to visualize an individual scientific output and use it for the purpose of wide range analysis. The software can help a researcher in the management of all steps of their scientific activity, effective communication and collaboration. Visual feedback can be considered as self-manager of scientific career. The authors also have presented their own approach towards visualizing thematic scope of publications with regard to knowledge domains space and drawn in a form of a ring wheel. The current research on software and implementation in academic environment is in progress.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130138632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Two-level dynamic index pruning","authors":"Jan Friedrich, C. Lindemann, Michael Petrifke","doi":"10.1109/ICDIM.2017.8244656","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244656","url":null,"abstract":"In this paper, we propose two-level dynamic index pruning for improving retrieval efficiency without degrading the quality of query results. Analyzing the ClueWeb09 data set, we observe that most terms appear in thousands of different websites, while internet search engines typically just display the top-10 search results. We conclude that retrieval efficiency would be substantially improved, if one could prune entire websites by knowing that the scores of all their web pages will not make it in the top-10 scores of the query. Thus, two-level dynamic index pruning utilizes a hierarchical document numbering scheme to subdivide posting lists into sorted runs of the pages of one website rather than the flat inverted index of all web pages. Experimental results on the ClueWeb09 data set illustrate the benefits of two-level dynamic index pruning for improving retrieval efficiency.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116017471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A content-constrained spatial (CCS) model for layout analysis of mathematical expressions","authors":"Xing Wang, Jyh-Charn S. Liu","doi":"10.1109/ICDIM.2017.8244694","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244694","url":null,"abstract":"This paper proposes a content-constrained spatial (CCS) model to recover the mathematical layout (M-layout, or MLme) of an mathematical expression (ME) from its font setting layout (F-layout, or FLme). The M-layout can be used for content analysis applications such as ME based indexing and retrieval of documents. The first of the two-step process is to divide a compounded ME into blocks based on explicit mathematical structure primitives such as fraction lines, radical signs, fence, etc. Subscripts and superscripts within a block are resolved by probabilistic inference of their likelihood based on a global optimization model. The dual peak distributions of the features to capture the relative position between sibling blocks as super/subscript call for a sampling based non-parametric probability distribution estimation method to resolve their ambiguity. The notion of spatial constraint indicators is proposed to reduce the search space while improving the prediction performance. The proposed scheme is tested using the InftyCDB data set to achieve the F1 score of 0.98.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116028569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rumor verifications on Facebook: Click speech of likes, comments and shares","authors":"A. Chua, Snehasish Banerjee","doi":"10.1109/ICDIM.2017.8244642","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244642","url":null,"abstract":"This paper seeks to answer the following research question: How do users of social networking sites react to rumor verifications? Rumor verifications refer to messages posted by Snopes, a website dedicated to verify rumors, to confirm the veracity of rumors as either true or false. Data were collected from Snopes' Facebook Fan Page. Users' reactions to rumor verifications on Facebook were examined through their click speech in the form of Likes, Comments and Shares. Users' reactions were studied as a function of two factors: rumor type (wish, dread or neutral), and verification verdict (true or false). Data analyses involved both quantitative and qualitative approaches. Results indicated that users' click speech of Likes and Shares differed significantly with respect to rumor type and verification verdict. Comments were found to contain personal opinion, emotive expression, and call-to-action. Based on these results, the paper offers four implications. It also points to a number of directions for future research.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123980104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pritish Patil, Jiayun Wang, Yuya Aratani, K. Kawagoe
{"title":"Prototyping a recommendation system for Ukiyo-e using hybrid recommendation algorithm","authors":"Pritish Patil, Jiayun Wang, Yuya Aratani, K. Kawagoe","doi":"10.1109/ICDIM.2017.8244658","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244658","url":null,"abstract":"This paper introduces a recommendation system for Ukiyo-e prints. Although there are some services available online which recommends Ukiyo-e prints to users, they have not supported a recommendation function, yet. To meet the complex preferences of the users, the hybrid algorithm can fit as a feasible solution to realize the Ukiyo-e recommendation. In this paper, our prototype recommendation system for Ukiyo-e using it is proposed. Our proposed system adapts item-based collaborative filtering, user-based collaborative filtering and popularity-based filtering to predict which Ukiyo-e prints the user may like to view. Also this paper addresses the cold start problem and ways to profile users when limited authentication information is available.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117283975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sharefah A. Al-Ghamdi, Joharah Khabti, Hend Suliman Al-Khalifa
{"title":"Exploring NLP web APIs for building Arabic systems","authors":"Sharefah A. Al-Ghamdi, Joharah Khabti, Hend Suliman Al-Khalifa","doi":"10.1109/ICDIM.2017.8244649","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244649","url":null,"abstract":"Natural language processing (NLP) is the branch of Artificial Intelligence that is concerned with enabling computers understand human languages. Implementing new NLP tools that effectively and efficiently process Arabic is not an easy task, usually such tools face challenges related to NLP various tasks. However, with the movement of many NLP companies to provide their NLP services via Web APIs, building NLP systems that can benefit from such APIs is becoming a reality. This paper will explore the available NLP Web APIs that supports Arabic language. It will also discuss their strengths and weaknesses and provide suggestion for future use.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126127068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daiki Namikoshi, Manabu Ohta, A. Takasu, J. Adachi
{"title":"CRF-based bibliography extraction from reference strings using a small amount of training data","authors":"Daiki Namikoshi, Manabu Ohta, A. Takasu, J. Adachi","doi":"10.1109/ICDIM.2017.8244665","DOIUrl":"https://doi.org/10.1109/ICDIM.2017.8244665","url":null,"abstract":"The effective use of digital libraries demands maintenance of bibliographic databases. Useful bibliographic information appears in the reference fields of academic papers, so we are developing a method for automatic extraction of bibliographic information from reference strings using a conditional random field (CRF). However, at least a few hundred reference strings are necessary to learn an accurate CRF. In this paper, we propose active learning and transfer learning techniques to reduce the required training data for CRFs. We evaluate extraction accuracies and the associated training cost by experiments.","PeriodicalId":144953,"journal":{"name":"2017 Twelfth International Conference on Digital Information Management (ICDIM)","volume":"133 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127431349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}