Entity Relationship Research Articles

MMKG-PAR: Multi-Modal Knowledge Graphs-Based Personalized Attraction Recommendation

As the tourism industry rapidly develops, providing personalized attraction recommendations has become a hot research area. Knowledge graphs, with their rich semantic information and entity relationships, not only enhance the accuracy and personalization of recommendation systems but also energize the sustainable development of the tourism industry. Current research mainly focuses on single-modal knowledge modeling, limiting the in-depth understanding of complex entity characteristics and relationships. To address this challenge, this paper proposes a multi-modal knowledge graphs-based personalized attraction recommendation (MMKG-PAR) model. We utilized data from the “Travel Yunnan” app, along with users’ historical interaction data, to construct a collaborative multi-modal knowledge graph for Yunnan tourist attractions, which includes various forms such as images and text. Then, we employed advanced feature extraction methods to extract useful features from multi-modal data (images and text), and these were used as entity attributes to enhance the representation of entity nodes. To more effectively process graph-structured data and capture the complex relationships between nodes, our model incorporated graph neural networks and introduced an attention mechanism for mining and inferring higher-order information about entities. Additionally, MMKG-PAR introduced a dynamic time-weighted strategy for representing users, effectively capturing and precisely describing the dynamics of user behavior. Experimental results demonstrate that MMKG-PAR surpasses existing methods in personalized recommendations, providing significant support for the continuous development and innovation in the tourism industry.

SISTEM INFORMASI PENYEWAAN TRUK BERBASIS WEB DI CV MAJU JAYA

Information Technology is a technology that is developing rapidly at this time. Progress in every field cannot be separated from technology as its support. Problems faced by CV. Maju Jaya is the unavailability of a web-based system as a medium for truck rental which has been done by customers. The method used to create this web-based truck rental system is to use the waterfall method as one of the system development methods, modeled and documented using Context Diagram designs, Data Flow Diagrams, Entity Relationship Diagrams, and PHP as the programming language used, as well as a MySQL database as computerized data storage and transactions. The result of this research is to create a web-based truck rental system at CV. Maju Jaya to make it easier to carry out rental transactions and publish information.
 

Effects of topological structure and destination selection strategies on agent dynamics in complex networks

We analyzed agent behavior in complex networks: Barabási–Albert, Erdos–Rényi, and Watts–Strogatz models under the following rules: agents (a) randomly select a destination among adjacent nodes; (b) exclude the most congested adjacent node as a potential destination and randomly select a destination among the remaining nodes; or (c) select the sparsest adjacent node as a destination. We focused on small complex networks with node degrees ranging from zero to a maximum of approximately 20 to study agent behavior in traffic and transportation networks. We measured the hunting rate, that is, the rate of change of agent amounts in each node per unit of time, and the imbalance of agent distribution among nodes. Our simulation study reveals that the topological structure of a network precisely determines agent distribution when agents perform full random walks; however, their destination selections alter the agent distribution. Notably, rule (c) makes hunting and imbalance rates significantly high compared with random walk cases (a) and (b), irrespective of network types, when the network has a high degree and high activity rate. Compared with the full random walk in (a) and (b) increases the hunting rate while decreasing the imbalance rate when activity is low; however, both increase when activity is high. These characteristics exhibit slight periodic undulations over time. Furthermore, our analysis shows that in the BA, ER, and WS network models, the hunting rate decreases and the imbalance rate increases when the system disconnects randomly selected nodes in simulations where agents follow rules (a)–(c) and the network has the ability to disconnect nodes within a certain time of all time steps. Our findings can be applied to various applications related to agent dynamics in complex networks.

Web-Based Outpatient Information System at RSUD Indramayu

This outpatient information system is a system that is run on the hospital outpatient unit to support the service process provided to patients used by the units that provide services. This outpatient information system assists hospitals in implementing an integrated and structured digitization of patient medical record data. The study aimed to produce an outpatient information system that provides convenience to hospital staff and patients in the process of health services in the outpatient unit of RSUD Indramayu. In this study, the author uses a descriptive method, which is a method that describes a situation or problem that is currently happening based on the facts and data obtained and collected at the time of carrying out the research. Outpatient information system design uses document flow, system flow, tiered diagrams, context diagrams, data flow diagrams, conceptual data models, and physical data models. The implementation of this research uses the PHP programming language and MySQL database as well as writing the system design using DFD (Data Flow Diagrams), namely Data Flow Diagrams, FlowMap, Flowcharts, and Entity relationship diagrams (ERD). The result of the research is an integrated web-based outpatient information system application from the beginning to the end of outpatient services for patients.

An Optimizing Business Process: A Comprehensive Analysis of Amazon Inc.’s Information Architecture

This analysis studies Amazon Inc.’s information system design in detail using context, use cases, test cases, class, and sequence diagrams. Our research aims to improve business processes by better understanding the system’s interactions, functionality, and data structure. The representation of data structure and entity relationships in class diagrams provides insights into the system’s component organization. Sequence diagrams also provide a clear picture of the sequential interactions between system elements, showing potential bottlenecks and optimization opportunities. It provides unique insights into Amazon’s approaches to keeping a competitive edge in the e-commerce industry, and it may be used as a resource for firms looking to improve their own information systems and procedures.

Development of a smart home suitability indicator and indicative self-assessment platform for the disabled facilities grants (DFGs)

Purpose Delay in housing adaptation is a major problem, especially in assessing if homes are suitable for the occupants and in determining if the occupants are qualified for the Disabled Facilities Grant (DFG). This paper describes the development of two self-administered intelligent integrated assessment tools from the DFG Adapt-ABLE system: (1) The Home Suitability Assessment Platform, which is a preventive mechanism that allows assessment of the suitability of homes based on occupants’ mobility status and (2) an indicative assessment platform that determines if the applicants are qualified for the DFG to prevent lengthy delays.Design/methodology/approach The adopted method aligned with a development study approach: a grounded literature review, a severity measurement approach, two stakeholder engagement workshops, four brainstorming sessions and four focus group exercises. The system development relied on Entity–Relationship Diagram (ERD) technique for data structures and database systems design. It uses DFG context sensitivity with alignment with DFG guidance, interlinkages and interoperability between the assessment tools and other platforms of the integrated Adapt-ABLE system.Findings The assessment tools are client-level outcomes related to accessibility, usability and activity based on the assessment process. The home suitability platform shows the percentage of the suitability of a home with assessment results that suggest appropriate action plans based on individual mobility status. The indicative assessment combines the function of referral, allocation, assessment and test of resources into an integrated platform. This enables timely assessment, decision-making and case-escalation by Occupational Therapists based on needs criteria and the eligibility threshold.Originality/valueThese assessment tools are useful for understanding occupants’ perception of their physical housing environment in terms of accessibility, suitability and usability based on basic activities of daily living and their mobility status. The indicative self-assessment tool will substantially cut down the application journey. The developed tools have been recommended for use in the CSJ Disability Commission report and the UK government Guidance on DFGs for local authorities in England.

Perancangan Sistem Informasi Akuntansi Penggajian Pegawai Instansi Pemerintah di BKPSDM Kab. Cianjur

The process of employee payroll system at BKPSDM Kab. Cianjur Agency already uses a computer but it is not optimal because it still uses Microsoft Excel in data collection and calculation salaries. The purpose of this research is to create a computerized payroll information system that make it easier for agency in the payroll process for employees and minimize the problems that often occur. This information system designed using PHP Myadmin programming language and MySQL as a database. The approach to developing this system uses the waterfall method and the tools involved include Flowmap, Context Diagram, Data Flow Diagrams (DFD), and Entity Relationship Diagrams (ERD). The results of this employee payroll application can make it easier to collect employee data and calculation of employee salaries accurately and can streamline time in making reports so as to reduce errors in the employee payroll system.

Information extraction from automotive reports for ontology population

In this paper, we showcase our research on the use of ontologies and information extraction for the purpose of modeling damages incurred on car bodies. With the increasing use of technology in the automotive industry, it is important to have a standardized and efficient way of documenting and analyzing car damage reports. Most existing reports are unstructured, and there is a lack of standardization in describing the damage. To address this issue, we have developed a domain ontology for car damage modeling (OCD),11 industryportal.enit.fr/ontologies/OCD,22 github.com/OntologyCarDamage/OCD and proposed an end-to-end system to extract information from French automotive reports. The information extraction process involves using named entity recognition (NER) and relationship extraction (RE) techniques to identify and extract relevant information from the reports. Then, the extracted information is used to populate the OCD ontology, allowing a structured and standardized representation of the damage information. The proposed system was tested on a real dataset of automotive reports and showed promising results.

Utilizing BERT for entity relationship extraction in Chinese medical texts

The Chinese medical sector has been somewhat lacking in knowledge graphs, a deficiency this study aims to address. By leveraging the prowess of the BERT pre-training model, a two-tier approach has been innovated that utilizes separate pre-trained encoders for both entity and relational models. These models are intricately linked: the output from the entity model seamlessly flows into the relational one, making it possible to adeptly extract entity relationships from Chinese medical texts. This research is anchored in the CMeIE dataset, sourced from the esteemed CHIP (China Health Information Processing) conference. This dataset stands as a recognized benchmark in evaluating Chinese medical texts. By harnessing this data, the methods have been rigorously tested and validated. The promising experimental results underscore the effectiveness of the approach in distilling relationships from Chinese medical literature. The implications of this research are profound. Beyond just enriching the Chinese medical domain, the boundaries of NLP technology are also being pushed. Potential applications are manifold: from constructing comprehensive Chinese medical knowledge graphs to assisting in early-stage medical diagnoses. This innovative approach not only addresses an existing gap but also sets the stage for future advancements in medical NLP.

Abstract B074: Novel targeting of semaphorin 7a-mediated endocrine therapy resistance in an immune competent ER+ breast cancer model

Abstract Estrogen receptor-positive (ER+) breast cancer (BC) comprises over 70% of all breast cancers and is the leading cause of BC-related deaths in women worldwide. Despite available therapies against ER+ BC, recurrence inevitably arises primarily due to therapeutic resistance. Our objective is to improve treatment strategies for patients with ER+ BC by studying the therapeutic targeting potential of semaphorin-7a (SEMA7A)-mediated endocrine therapy resistance in an immune competent model of ER+ breast cancer. It is known that SEMA7A, a neuronal guidance protein that is dysegulated in several cancer types, confers poor prognosis and survival in BC patients, is regulated by ER, activates integrin-mediated PI3K/AKT signaling and promotes resistance to the ER-targeted therapies. In the normal mammary gland, SEMA7A binds β1- and a6-integrin to activate pathways including pro-survival PI3K/AKT signaling, which is known to promote tumor cell survival and multi-drug resistance. Using reverse phase protein array we identified differential expression between empty vector (EV) or SEMA7A-overexpressing (OE) MCF7 cells. SEMA7A OE cells had increased survival signaling proteins (pAKT, pS6K, pPTEN, pFAK, pSrc, pmTOR). Other protein types upregulated included cell adhesion (E-Cadherin), signal transduction (ITGB1, STAT3, ITGB4, NFkB, ILK1) and regulation of cell death/survival (BCL2, RB1, Annexin1). We validated that SEMA7A-induced signaling activates AKT in ER+ BC cells, and that inhibition of PI3K via alpelisib (Novartis) and GCT-007 (Global Cancer Technology) reduces tumor growth in vitro and in vivo in a MCF7/NCG xenograft model. Our preliminary studies show that SEMA7A OE tumors in NCG mice respondly poorly to fulvestrant, while EV tumors are sensitive. Further, PI3K inhibition by alpelisib or GCT-007 rendered SEMA7A OE, fulvestrant-resistant tumors sensitive to treatment in this model (n=5/group). Our lab has also created an anti-SEMA7A monoclonal antibody (SmAb) that directly targets SEMA7A. Our results show that SmAb inhibits tumor growth in triple negative mouse BC mouse models, but is less effective in immunocompromised models. Since our data show that SmAb restores anti-tumor immunity, we sought to inhibit the SEMA7A-integrin-PI3K/AKT pathway in an immune competent ER+ model. Therefore, utilized a novel syngeneic ER+ preclinical model comprised of TC11 murine tumor cells, which express SEMA7A, and FVB/N mice. Mice were treated with tamoxifen, and after tumors did not respond, PI3K inhibitors were initiated, which slowed tumor growth but did not achieve full regression. Our findings show that the addition of either PI3K inhibitor (alpelisib or GCT-007) to tamoxifen was more effective than tamoxifen alone. Future studies will investigate the combinations with SmAb and identify immune-related effects after PI3K/SEMA7A inhibition. If effective, our studies would suggest that ER+ SEMA7A+ patient tumors should be considered for PI3K/SEMA7A-targeted therapies. Citation Format: Rachel N Steinmetz, Lyndsey S Crump, Traci R Lyons. Novel targeting of semaphorin 7a-mediated endocrine therapy resistance in an immune competent ER+ breast cancer model [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B074.

Abstract B007: Vandetanib abrogates antiestrogen resistance in MAPK-driven ER+ breast cancer by halting key intracellular signaling pathways and multiple druggable kinases

Abstract Introduction: Vandetanib has been shown to abrogate ER+ breast cancer growth via inhibition of MAPK; we sought to elucidate the effects of Vandetanib on MAPK-driven endocrine-resistant breast cancer. Methods: Chronically treated MCF7-TAM (Tamoxifen), MCF7-EXE (Exemestane), and wild-type MCF7 ER+ breast cancer cell lines were treated with Vandetanib and/or Tamoxifen. Cell viability assays were conducted with CellTiter-Glo. Cells were treated with Vandetanib (10 uM) and vehicle for 24 hours, and mRNA sequencing was performed. To elicit TKI-specific proteomic changes, cells were treated with control or IC90 Vandetanib for 48 hours, and the signatures of kinase activity were determined using a multiplex inhibitor bead library coupled with mass spectrometry. Differential gene (DGE) and protein (DPE) expression analyses were performed to determine enriched and depleted transcripts and kinase activity with Vandetanib treatment. Gene set enrichment analysis was performed to determine the shared and unique pathways regulated by Vandetanib for each model. A Vandetanib response signature was compiled using the top 20 downregulated genes and analyzed with METABRIC and SCAN-B datasets to assess effects on survival in ER+ breast cancer patients. Results: MCF7-TAM and MCF7-EXE demonstrated lower Tamoxifen IC50 when treated with Vandetanib compared to Tamoxifen alone, which showed synergistic effects. Data analysis of mRNA libraries showed reduced tumor progression and signaling of MAPK, PI3K/AKT, RAS, CCND1, MYC, and EGFR across all three lines, as well as increased ERBB2 signaling, which may denote a potential adaptive bypass mechanism to Vandetanib treatment. Gene sets showed increased estrogen response, ESR1 activity, and sensitivity to tamoxifen across all three lines. Notable key players in PI3K/AKT and MAPK signaling such as TYRO3 were significantly downregulated at both the gene and protein levels. Additionally, JAK2 demonstrated dual upregulation and has been implicated with favorable prognosis due to associations with immune infiltration. The downregulated Vandetanib gene set conferred significantly improved OS (HR=0.75, p<0.0001, METABRIC; HR=0.87, p=0.034, SCAN-B) and RFS (HR=0.60, p<0.0001, METABRIC) in ER+ breast cancer patients from both datasets. Multiple druggable kinases such as RET, EGFR, FGFR2/3, CDK6, and SRC were depleted by Vandetanib treatment. Upregulated druggable kinases identified with Vandetanib treatment include MTOR, FGFR4, ERBB2, and JAK1. Conclusions: Vandetanib overcomes antiestrogen resistance in MAPK-driven models of ER+ breast cancer by halting key signaling pathways such as MAPK, PI3K/AKT, MYC, and ERBB2, among others. Upregulated druggable kinases may serve as targets to overcome resistance to Vandetanib. Downregulated targets with Vandetanib could serve as biomarkers to select patients most likely to benefit from Vandetanib treatment. Citation Format: Rasha T Kakati, Austin Whitman, Hyunsoo Kim, Philip M Spanheimer. Vandetanib abrogates antiestrogen resistance in MAPK-driven ER+ breast cancer by halting key intracellular signaling pathways and multiple druggable kinases [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B007.

Abstract A079: Loss of BPTF restores estrogen-regulated programs and suppress metastatic development of mammary tumors

Abstract Chromatin remodeling controls transcriptional programs that drive mammary epithelial lineage commitment and cellular differentiation. This process is also important for the regulation of highly dynamic cellular states during mammary tumorigenesis, and perturbing the chromatin landscape of cancer cells can halt cellular and molecular mechanisms of mammary cancer development and progression. However, this paradigm assumes that all cancer cells that develop in the mammary tissue bear the same chromatin dependencies, and rely on similar programs throughout cancer progression. Here, we show that molecular dependencies regulated by the epigenetic factor BPTF control tumor development and progression across distinct mammary cancer cell states. With the utilization of classical models of mammary tumorigenesis, single cell transcriptional profiling, and organoid cultures, we demonstrate that BPTF loss results in the development of mammary tumors with a longer latency of ER•+ expression and tamoxifen sensitivity and the inhibition of lung metastasis development. While gain of ER• expression was associated with gain of luminal markers in Krt5+ BPTF KO mammary epithelial cells (MECs), metastasis-like signatures were significantly perturbed in cells with defined luminal fate. In addition, we detected a partial rescue of metastatic features via the activation of transcriptional programs controlled by TGF-•, thus indicating that BPTF sits atop a canonical metastatic pathway. Collectively, our studies illustrate how BPTF-specific chromatin remodeling inhibition induces phenotypes that differentially affect tumor development and progression, while allowing for the development of a murine model of ER•+ mammary tumorigenesis. Citation Format: Chen Chen, Michael F. Ciccone, Marygrace c. Trousdell, Deeptiman Chatterjee, Yixin Zhao, Steven M. Lewis, Dhivya Anandan, John E. Wilkinson, William C. K. Pomerantz, Adam Siepel, Camila O. dos Santos. Loss of BPTF restores estrogen-regulated programs and suppress metastatic development of mammary tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A079.

Investigation on survivability of the entity investing in integrated energy system service under contract for difference

As an important measure of promoting renewable energy sources (RESs), Integrated Energy System (IES) has caused wide concern. However, investors are staying on the sidelines due to the shortage of the details about investment returns. Therefore, here investigates the survivability of investment entity in Chinese IES service under contract for difference (CFD). Integrated with the intricate relationship of different entities, here constructed three evaluation models including the dynamic payback period (DPP), net present value (NPV) and internal rate of return (IRR). Considering the multipath feature of IES operation, the priority of energy utilization is proposed to promote RES consumption. According to the existing circumstance of RESs and IES, 12 operation scenarios are classified to investigate economic benefit of investment entity. Plenty of simulations show that the project benefit is affected by the contract tariff risk bigger, by the contract cycle risk slighter. Also, RESs absorption rate and RESs increase have significant influence on the investment benefits. The performances of IES with combined supply mode (CSM) are superior to that with sub-supply mode(SSM). With Chinese existing technologies and policies, the optimal scenario is S2 of which the payback period is about 6.38 years, and the internal rate of return is 18.47 %.

DESIGN OF INVENTORY MONITORING INFORMATION SYSTEM OF OFFICE EQUIPMENT AND SUPPLIES AT BAZNAS CITY OF BANDUNG BASED ON MACRO EXCEL (VBA)

BAZNAS, the National Amil Zakat Agency, is the official institution overseeing zakat management at the national level. In Bandung City, BAZNAS runs programs such as Healthy Bandung, Smart Bandung, Taqwa Bandung, and Caring Bandung, contributing to the city's prosperity. To streamline office operations, related institutions must conduct inventory activities for office equipment and supplies. However, BAZNAS Bandung City currently employs a manual inventory management system, involving paper-based recording, recapitulation, and individual input into Excel sheets, leading to inefficiency, security concerns, and data loss risks. Recognizing the need for improvement, a new information system has been designed using Microsoft Excel, Macros, and Visual Basic Applications. The design includes Data Flow Diagrams and Entity Relationship Data to enhance the management and monitoring of inventory data, ensuring data integrity and structured inventory activities. Project evaluations, following the End User Computing Satisfaction (EUCS) principle, show that the system meets institutional needs and is user-friendly. Users are provided with a manual book during testing to enhance system understanding. While the trial results are positive, constructive feedback suggests the need for further feature enhancement to ensure smoother system operation and greater overall benefits. This information system aims to speed up and simplify inventory data management, bringing efficiency to BAZNAS Bandung City's operations.

Perancangan Sistem Informasi Perpustakaan Berbasis Web Pada UPT SMP Negeri 34 Gresik

Technical advances in computer applications have led to the creation of these library information systems, which are anticipated to support and facilitate the human workforce. It is anticipated that this technology will help with daily tasks in an effective and efficient manner as well. The subject of this study is the library system. There are obstacles in UPT Library SMP 34 GRESIK, and one of them is that the library still uses its service manual procedures, indicating the need innovation and change in the form of a cohesive system to accompany and prepare children in the classroom The library service information system provided by this network-based library information system should make it easier for students to find information and check out books, as well as for librarians to manage information about books and student loans. The waterfall approach was used by the author. To create this internet-based library resource system. The process of implementing this library information system begins with soft requirement analysis, prioritizing the process of borrowing books. Waterfall design techniques are used throughout the design stage, which involves creating a database with MySQL and building a user interface. Relationships are built in the database architecture using Entity Relationship Diagrams and Logic Relationship database (Database) structures.

A Study of Entity Relationship Extraction Algorithms Based on Symmetric Interaction between Data, Models, and Inference Algorithms

The purpose of this paper is to address the extraction of entities and relationships from unstructured Chinese text, with a particular emphasis on the challenges of Named Entity Recognition (NER) and Relation Extraction (RE). This will be achieved by integrating external lexical information and utilizing the abundant semantic information available in Chinese. We utilize a pipeline model that is applied separately to NER and RE by introducing an innovative NER model that integrates Chinese pinyin, characters, and words to enhance recognition capabilities. Simultaneously, we incorporate information such as entity distance, sentence length, and part-of-speech to improve the performance of relation extraction. We also delve into the interactions among data, models, and inference algorithms to improve learning efficiency in addressing this challenge. In comparison to existing methods, our model has achieved significant results.

Legal Complications Relating to Things Outside Commerce: A Overview from Past to Present. Based on the Lottery Case in the State of Mizoram

Abstract: “Res Extra Commercium” is a Roman law doctrine that translates to “things outside commerce”. In State of Bombay v R.M.D. Chamarbaugwala , Justice Das introduced this doctrine into the Indian jurisprudence. The doctrine was introduced to constrict the scope of freedom of trade and commerce, a fundamental right, guaranteed under Article 19(1)(g) of the Indian Constitution. It constricts the scope by excluding certain “immoral” or “noxious” trade activities from the scope of Article 19(1)(g) and thereby, depriving them of Constitutional protection. The doctrine of res extra commercium seeks to exclude certain activities from the ambit of freedom of trade and profession guaranteed under Articles 19(1)(g) and 301 of the Constitution of India. Tracing back the origin of the doctrine to Roman Law has commented to the effect: The res extra commercium doctrine traces its conceptual roots to Roman law. Res in commercio, in Roman law, were things capable of ownership and hence, the subject of property rights, while res extra commercium were things incapable of ownership. In light of this, the doctrine applies to those things that are not objects of commerce i.e., they are extra commercio. In Justinian’s Institutes of Roman Law, only three classes of entity are conceptually treated as res extra commercium:

Joint extraction model of entity relations based on decomposition strategy

Named entity recognition and relation extraction are two important fundamental tasks in natural language processing. The joint entity-relationship extraction model based on parameter sharing can effectively reduce the impact of cascading errors on model performance by performing joint learning of entities and relationships in a single model, but it still cannot essentially get rid of the influence of pipeline models and suffers from entity information redundancy and inability to recognize overlapping entities. To this end, we propose a joint extraction model based on the decomposition strategy of pointer mechanism is proposed. The joint extraction task is divided into two parts. First, identify the head entity, utilizing the positive gain effect of the head entity on tail entity identification.Then, utilize a hierarchical model to improve the accuracy of the tail entity and relationship identification. Meanwhile, we introduce a pointer model to obtain the joint features of entity boundaries and relationship types to achieve boundary-aware classification. The experimental results show that the model achieves better results on both NYT and WebNLG datasets.

Aplikasi IT Support Work Orders Berbasis Web Dalam Rangka Menuju Sidoarjo Smart City

One important aspect in supporting the smart city concept is adequate information technology infrastructure. The Sidoarjo district government has made many innovations in making this happen, one of which is the construction of an intranet and internet network using fiber optics which is centered in the Data Center and managed by the Sidoarjo District Communication and Information Center. As a work unit in the field of ICT infrastructure and security at the Sidoarjo Regency Diskominfo, it is responsible for serving reports from the OPD (Regional Apparatus Organization) regarding intranet and internet network problems in the Sidoarjo regency environment. However, the reporting system used is still very simple and manual. The aim of this research is to design and build a web-based system that functions as a complaint, documenting work, and reporting handling related to intranet and internet network problems at the OPD in Sidoarjo Regency. In collecting data, this research used qualitative methods. Meanwhile, system development uses the System Development Life Cycle (SDLC) method with waterfall model, and uses Unified Modeling Language (UML) and Entity Relationship Diagram (ERD) as system modeling. This application was built using PHP with the CodeIgniter framework and MySQL. The results of this research show that the system makes it easier for related parties to make complaints, document work, and report handling.

Predicting Chinese tourists’ B&B preferences through a method of online reviews causality analytic

With the enormous numbers of online reviews posted daily, automatically acquired and analyzed the information that rich of causal logics is of great significance for Chinese B&B enterprises to make accurate business decisions. This study proposed a method based on Chinese NLP technologies to reveal and describe the formation process of tourists' behavioral preferences better than the previous entity relationship extraction and analysis methods. Firstly, Cause-effect syntactic and template pattern had been applied to extraction event casual relations in the online reviews texts. Then, Doc2vec-Kmeans clustering algorithm and key-phrases sorting algorithm were used to generalize data. Finally, causality graph was constructed for visual analysis. To evaluate the performance of the proposed approach, we collected 549, 732 Chinese B&B reviews from Ctrip.com and Qunaer.com. The survey identified 7 common preferences that travelers' concern about nowadays and reveals the reasons behind each of them, as well as concluded that the ‘services’ and ‘conveniences’ of Chinese B&Bs are the trends of travelers’ preferences in the future selections. The results indicated that the proposed approach outperforms the other entity relation extraction method in event forecasting, and most of the subjects believed that the proposed approach can provide more comprehensive and logical traveler's potential demand information.