Browsing Method Research Articles

Research on the Method of Managing Personal Massive Photos Using Geodatabase

Abstract. In view of the limitations of the existing methods for personal massive photos management and browsing, a method of using geodatabase to manage and browse massive personal photos is proposed. Firstly, vector geodatabase is created and defined based on geographic information technology. Then, attribute information including the file name, photo date and time, photo point longitude, photo point latitude, location name, photo storage path and so on of each photo in the file system are extracted. Finally, based on the longitude and latitude of the photo point, the geospatial location data of each photo is generated, and written into the vector geodatabase together with the attribute information. Based on the storage path of photos in the file system, the links between the geospatial database and photos are established. Furtherly realize the attribute information and geographical space location management of massive photos, as well as the browsing and viewing of photos. Take personal photos as an example to introduce the data processing and verify the practicability of the method. The result shows that this method uses the idea of geodatabase to manage massive personal photos, which is conducive to reflect the geographical spatial distribution and density characteristics of the photos, and can use the time axis to connect the track of personal history, which is convenient for browsing and analyzing the experience.

The New Ecology of Chinese Language and Literature in the Digital Age--Cultural Inheritance and Innovation

Abstract Digital media is perpetually evolving, significantly impacting the Chinese language and literature. Concurrently, the rapid pace of modern lifestyles poses challenges to the transmission of cultural heritage within Chinese literary traditions. Accordingly, this study explores the pathways for digital innovation in Chinese literature, focusing on the integration of key virtual technologies to facilitate the cultural inheritance of the Chinese language. This research highlights the application of advanced virtual technologies in preserving and transmitting Chinese linguistic culture. It involves designing an experiential process for cultural inheritance, utilizing these technologies to process graphic and textual information pertinent to the Chinese language and literature. Furthermore, the study innovates cultural transmission methods through the synthesis of virtual 3D scenes and the implementation of human-computer interaction functionalities. An experimental evaluation approach was employed to assess the impact of virtual reality technology on the learning outcomes in Chinese literature and its cultural transmission. The findings indicate that users who interactively engage with the content in a virtual environment achieve a learning effect score that is 0.6528 points higher than those using traditional browsing methods. This underscores the enhanced efficacy of interactive experiences in facilitating the learning of Chinese literature. The regression analysis further demonstrates the significant promotional effects of the number of virtual experiences in Chinese literature (P1) and the rate of user interaction with computers (P2) on the dissemination of Chinese cultural content. The fixed and random effects for the number of virtual experiences are 0.9428 and 0.9784, respectively, while those for user interaction rates are 0.8945 and 0.8835. These results suggest a substantial impact on the broader dissemination and transmission of Chinese language literature, reinforcing the value of integrating virtual reality technologies in cultural education.

PENERJEMAHAN E-BOOKLET INFORMASI WISATA ALAM CURUG YANG DIKELOLA OLEH PERUM PERHUTANI KPH BANYUMAS TIMUR KE DALAM BAHASA MANDARIN

Curug nature tourism managed by Perum Perhutani KPH East Banyumas currently only has information services in Indonesian, so that information about the tour has not spread to foreign visitors. The Curug nature tourism information e-booklet in Mandarin aims to improve information services for Curug nature tourism managed by Perum Perhutani KPH East Banyumas for Chinese-speaking visitors. In making an information e-booklet for nature tourism Curug in Mandarin, the data collection techniques used were the observation method, the interview method and the internet browsing method. In the process of translating the information e-booklet on Curug natural tourism in Mandarin, three stages were used, namely analysis, transfer and restructuring. The method used is the communicative translation method. The results of the translation of the e-booklet of Chinese-language Curug nature tourism information will be uploaded on Weibo and Instagram social media, because Weibo and Instagram are social media that are easily accessible by Chinese-speaking visitors. Chinese-language e-booklets can help foreign visitors, especially Chinese-speaking visitors, to obtain information regarding natural tourist attractions managed by Perum Perhutani KPH East Banyumas. Keyword: mandarin language, e-booklet, translation, nature tourism.

Unreal memories

Images of architecture spread quickly on visual social networks that gain interest to disseminate and communicate architecture. For this reason, it is a must to diagnose the social construction of the image of architecture, to explore the restrictions and publication formats of the platform, to identify the reaction and dissemination habits in relation to the visual features of photography and to delve into the possibilities and the risks introduced by artificial intelligence systems. The research method follows a cognitive association approach through various graphic case studies on Instagram. The exploratory design to approach the role of the image to communicate architecture in visual social media arises from the concept of the fragment and the biased vision, a division required due to the nature of related image suggestions as a browsing method on Instagram. The findings identify opportunities and action strategies to complement the contents that build the collective image of architecture adapted to the logic of the new scenario.

Application of Seismic Stratigraphic Slice Continuous Browsing Technology to Delicately Characterize River Sedimentary Microfacies

On the basis of understanding the regional tectonics characteristics and stratigraphic sedimentary characteristics of the study area, the sequence stratigraphic framework within the region is gradually studied by applying the principle of high-resolution sequence stratigraphy, and G4 oil formation is divided into three sets of sand formations, namely, G4 upper, G4 middle, and G4 lower sand formations, and divided into small layers in detail. Through comprehensive analysis of lithofacies, logging facies, and seismic facies, the sedimentary facies of the G4 oil formation are comprehensively analyzed. The main sedimentary facies type of the G4 oil formation is the delta front facies belt, and the most important sedimentary microfacies in the delta front facies belt are underwater distributary channel sedimentary microfacies. Using seismic sedimentology methods, make stratigraphic slices of each sub layer of the G4 oil formation, and use the rapid browsing method of stratigraphic slices to trace river sand in detail.

Sistem Pengarsipan Digital pada Dinas Kelautan Provinsi NTT

The Digital Archiving System at the Marine Service of East Nusa Tenggara Province in archiving incoming mail, outgoing mail active and inactive archives is still manual by being recorded in the agenda book which makes it difficult to find files. It aims to create a filing system for incoming mail, outgoing mail, active archives and inactive archives to facilitate archiving and searching. The research method used is the method of interview, observation, literature study and internet browsing, while for application development the method used is the Waterfall method. The software used is windows 10, Visual Studio code, Xampp Control Panel v3.2.2 PHP, mysql. The results of the application that are built are expected to help the Department and also for website visitors.
 
 Keywords: Archiving system, incoming mail, outgoing mail, PHP active and inactive archives, mysql

Session-Based Recommendations for e-Commerce with Graph-Based Data Modeling

Conventional recommendation methods such as collaborative filtering cannot be applied when long-term user models are not available. In this paper, we propose two session-based recommendation methods for anonymous browsing in a generic e-commerce framework. We represent the data using a graph where items are connected to sessions and to each other based on the order of appearance or their co-occurrence. In the first approach, called Hierarchical Sequence Probability (HSP), recommendations are produced using the probabilities of items’ appearances on certain structures in the graph. Specifically, given a current item during a session, to create a list of recommended next items, we first compute the probabilities of all possible sequential triplets ending in each candidate’s next item, then of all candidate item pairs, and finally of the proposed item. In our second method, called Recurrent Item Co-occurrence (RIC), we generate the recommendation list based on a weighted score produced by a linear recurrent mechanism using the co-occurrence probabilities between the current item and all items. We compared our approaches with three state-of-the-art Graph Neural Network (GNN) models using four session-based datasets one of which contains data collected by us from a leather apparel e-shop. In terms of recommendation effectiveness, our methods compete favorably on a number of datasets while the time to generate the graph and produce the recommendations is significantly lower.

Exploring natural language processing techniques to extract semantics from unstructured dataset which will aid in effective semantic interlinking

Designing efficacious semantics for the dynamic interaction and searches has proven to be concretely challenging because of the dynamically of the semantic searches, method of browsing and visualization interfaces for high volume information. This has a direct impact on enhancing the capabilities of the web. To surmount the challenges of providing meaning to high volume unstructured datasets, Natural language processing techniques and implements have been proven to be propitious, however, the reactivity of these techniques should be studied and predicated on the objective of providing meaning to the unstructured data. This paper demonstrates the working of five NLP techniques namely, bag-of-words, TF-IDF, NER, LSA, and LDA. The experiment provides the kindred attribute accomplishment or the identification of the meaning of this unstructured data varies from one technique to another. However, NLP techniques can be efficient as they provide insights into the data and make it human-readable. This will in turn avail in building better human–machine intractable browsing and applications.

Manifold Learning Methods for Visualization and Browsing of Drum Machine Samples

Manifold Learning Methods for Visualization and Browsing of Drum Machine Samples

Query Driven Conceptual Browsing: A Semi-Automated Approach for Building and Exploring Concepts on the Web

The presence of communities, which are groups of highly cross referenced pages together representing a single concept, is a striking feature of the World Wide Web. Quite often a group of communities, each topically coherent within itself, may be related through a common concept manifested in each of them. Motivated by this observation, we present a method for query-driven conceptual browsing for exploring concepts on the Web starting from a user-specified query. We show how this idea is related to prior work on learning concept maps and on Web Mining, and discuss the application of conceptual browsing for user-driven exploration and discovery of new concepts on the Web.

Data Cleaning Utilizing Ontology Tool

Recent advancement in Internet Technologies has made web browsing increasingly easy and user friendly. From the traditional method of desktop web browsing and the birth of dial up modem connection, users nowadays are able to enjoy a fast and reliable web browsing via high speed wireless Internet connection and portable mobile devices. Browsing a web has become much easier with the state of the art search engines such as Google, which provide much functionalities which could make browsing easier such as improved crawler, easy to use search interface, web personlization, Web 3.0 support and integration and many more. In order to build a robust and reliable search engine, the developer needs to integrate all the data and present them in a meaningful format for user’s viewing convenience. Integrating these data is a tedious task as data usually occur in numerous format, and layout. Furthermore, web developers usually present the data content in various languages of their choice, which made the processing of these data increasingly difficult. There is also no standard convention to represent the data format and even a standardize rule to process this data has not been developed. To resolve this issue, researchers develop data extractor which could effectively extract data from web sources, tabulate them, and used it for further processing. However, not all data are correctly extracted, they may either missed certain valuable information or contain additional unnecessary information. In the case of unnecessary information, researchers use a cleaning method to remove them such that the data extracted are free of errors. Removing these data is important as unnecessary information may affect the accuracy of subsequent extractor tools, hence may eventually prevent the tool from performing its task efficiently. In this research proposal, we embark on a data cleaning tool to clean data using ontology tools. Experimental results show that our tool is highly efficient in data cleaning and is able to outperform existing state of the art tools.

Human motion capture data retrieval based on semantic thumbnail

We present a method for the efficient retrieval and browsing of immense amounts of realistic 3D human body motion capture data. The proposed method organizes motion capture data based on statistical K-means (SK---means), democratic decision making, unsupervised learning, and visual key frame extraction, thus achieving intuitive retrieval by browsing thumbnails of semantic key frames. We apply three steps for the efficient retrieval of motion capture data. The first is obtaining the basic type clusters by clustering motion capture data using the novel SK-means algorithm, and after which, immediately performing character matching. The second is learning the retrieval information of users during the retrieval process and updating the successful retrieval rate of each data; the search results are then ranked on the basis of successful retrieval rate by democratic decision making to improve accuracy. The last step is generating thumbnails with semantic generalization, which is conducted by using a novel key frame extraction algorithm based on visualized data analysis. The experiment demonstrates that this method can be utilised for the efficient organization and retrieval of enormous motion capture data.

Knowledge map-based method for domain knowledge browsing

The exponential growth of available information and the deployment of knowledge management systems delivers excessive information to the end users that they cannot manage at once. This problem has led to an increased emphasis on solutions to information overload. Searching and browsing are two methods to locate information. Many studies have focused on solving the information overload problem in the searching process, but the methods to alleviate information overload in browsing process have not been adequately studied. Hence, a method that addresses information overload in the browsing process is presented in this paper. The aim is to reduce the information overload during browsing domain knowledge for new knowledge users who have little understanding of the information. In this method, a knowledge map and social network analysis are utilized to navigate the knowledge users. Technologies first construct a knowledge map from text mining and the important knowledge that includes more information about the domain is then identified via social network analysis. Based on this process, the knowledge user can browse the domain knowledge starting from the important knowledge and navigate via the knowledge map. We applied the method to assist new knowledge users in browsing the Computer Numerical Control (CNC) domain knowledge base to validate the method. The results indicate that the method can identify the important knowledge at a highly acceptable level, the constructed knowledge map can efficiently navigate the knowledge users, and the information overload can be significantly decreased.

A Study on Resources and Services in the Nursing College Libraries at Bangalore City, Karnataka

Education is the transmission of civilization. Well educated and skilled people are key to creating, sharing and disseminating knowledge effectively. It is as old as the history of mankind. It forms the basis for the development and progress of individual and human society. Importance of human resources and the role of education in development has been well recognized. Education is considered as critical input for economic and social development. It is an instrument to imparting knowledge and training to people leading to thei empowerment. Majority of the library were users are satisfied with the availability of textbooks and magazines followed by periodicals and general books. Inadequacy of electronic resources was stated by some users. The number of multiple copies is not enough. There should be more books by Indian authors. The users of the library were asked to indicate how they find required reading material and books. Majority of the users said it is by browsing through the shelves. Some said they consult the library staff and seek their help in finding books. Some students admitted that they take help from their class fellows. A few users said that they use catalogue to locate books. This infers that the methods followed by the students to find the required books in the libraries vary. Majority of the students who use the library stated that catalogue is not upto- date. A high percentage of library users follow the method of browsing and checking the racks and consulting the library staff.

λ-diverse nearest neighbors browsing for multidimensional data

Traditional search methods try to obtain the most relevant information and rank it according to the degree of similarity to the queries. Diversity in query results is also preferred by a variety of applications since results very similar to each other cannot capture all aspects of the queried topic. In this paper, we focus on the \lambda-diverse k-nearest neighbor search problem on spatial and multidimensional data. Unlike the approach of diversifying query results in a postprocessing step, we naturally obtain diverse results with the proposed geometric and index-based methods. We first make an analogy with the concept of Natural Neighbors (NatN) and propose a natural neighbor-based method for 2D and 3D data and an incremental browsing algorithm based on Gabriel graphs for higher dimensional spaces. We then introduce a diverse browsing method based on the distance browsing feature of spatial index structures, such as R-trees. The algorithm maintains a Priority Queue with mindivdist of the objects depending on both relevancy and angular diversity and efficiently prunes nondiverse items and nodes. We experiment with a number of spatial and high-dimensional data sets, including Factual's (http://www.factual.com/) US points-of-interest data set of 13M entries. On the experimental setup, the diverse browsing method is shown to be more efficient (regarding disk accesses) than k-NN search on R-trees, and more effective (regarding Maximal Marginal Relevance (MMR)) than the diverse nearest neighbor search techniques found in the literature.

Movie browsing system based on character and emotion

A variety of research is in progress to detect wanted scenes from videos. A method of detecting scenes wanted by a user through scene rearrangement based on calculated visual similarity is limited in that such a method does not reflect elements along the storyline through which a user remembers a movie. A movie's story is built up by characters, and such build-up is closely related with emotions of characters in a film. A movie browsing system based on storyline is executable by applying characters and those characters' emotions. Thus, methods of extracting key characters in each scene and of clustering scenes through extraction of emotion vectors from dialogues in each scene are hereby suggested. This paper also proposes to develop a movie browsing method and a system based on emotions of characters.

SymbolChat: A flexible picture-based communication platform for users with intellectual disabilities

Persons with intellectual disabilities benefit from participating in the modern information society, especially the World Wide Web, social media and Internet-mediated communication services. Although several computer-based prototypes and commercial systems have been introduced for accessible in-person communication, currently few applications and services exist to support synchronous remote communication for this user group. We introduce SymbolChat, a software platform that supports the creation of multimodal communication applications utilizing picture-based instant messaging. End users and their support personnel can customize the input and output features of the application based on their individual needs and abilities. The interaction is based on touchscreen input and speech output using speech synthesis technology. The SymbolChat platform was developed together with the prospective end users and practitioners in the field of special needs care.We evaluated the prototype application in a field study with nine users with varying degrees of intellectual and other disabilities. The results clearly indicate that the participants were able to express themselves in spontaneous communication using a large-scale picture-based vocabulary (around 2000 symbols) even without prior training in the use of symbols. This finding was supported in the constructive feedback gathered from professionals working in the area. We also successfully applied methodology from other settings, such as child-computer interaction to evaluate interaction in this challenging context.Overall, the results show that social inclusion for people with intellectual disabilities can be improved with customizable communication tools. The implemented communication platform forms a solid basis for further improvements and new communication services. In addition, we found that users with motor impairments would greatly benefit from alternative input and output methods for symbol browsing and selection.

Collaborative browsing system based on semantic mashup with open APIs

Due to a large amount of information available on world wide web, it has been difficult for users to effectively find relevant information. Many web browsing methods and systems have been investigated to apply adaptive approaches which can extract personal interests of the users. In this paper, we propose a semantic mashup-based collaborative browsing (co-browsing) platform for supporting knowledge sharing with other partners. Especially, the semantic mashup scheme can integrate heterogeneous information collected by various Open APIs, and help users to determine which partners should be selected. For evaluating the proposed method, we have implemented a co-browsing platform which can exchange bookmarks, and measured whether the semantic mashup scheme make a positive influence on improving the performance of the co-browsing process.

ContextGrid: A contextual mashup-based collaborative browsing system

Due to a large amount of resources (i.e., information and knowledge) available on world wide web, it has been more difficult for users to effectively find relevant web resources. Most of the current web browsing methods and systems have been investigated to apply adaptive approaches which can extract personal contexts (e.g., interests and preferences) of the users. In this paper, we propose a contextual mashup-based collaborative browsing (co-browsing) platform, called ContextGrid, for providing online users with various knowledge sharing services. Particularly, the proposed mashup scheme can integrate heterogeneous pieces of information collected by various Open APIs, and assist the users to decide which partners should be selected for mutual collaborations. In order to evaluate the proposed mashup-based method, we have implemented a co-browsing platform which can exchange bookmarks, and measured whether the contextual mashup scheme makes a meaningful influence on improving the performance of the co-browsing process with multiple users.

Automated Generation of Personal Data Reports from Relational Databases

This paper presents a novel approach for extracting personal data and automatically generating Personal Data Reports (PDRs) from relational databases. Such PDRs can be used among other purposes for compliance with Subject Access Requests of Data Protection Acts. Two methodologies with different usability characteristics are introduced: (1) the GDSBased Method and (2) the By Schema Browsing Method. The proposed methdologies combine the use of graphs and query languages for the construction of PDRs. The novelty of these methodologies is that they do not require any prior knowledge of either the database schema or of any query language by the users. An optimisation algorithm is proposed that employs Hash Tables and reuses already found data. We conducted several queries on two standard benchmark databases (i.e. TPC-H and Microsoft Northwind) and we present the performance results.