Lazy Loading Based with Load On Demand and Currency Support in Web Browser

In this work our goal is to make a Web client application for the Real Estate Business. We already have a Stand-Alone Application for the same, so we are migrating from Online Application to the Web Client. Here for this we are using XPA tool which is a tool to move a project and make changes as per necessity. During this, we designed the editing function size and position adjustment, hiding and displaying, style editing, editing by device type etc. for every device type such that the contents will be dynamically converted according to resolution or screen-size in step with various devices. To be able to answer various devices, storing device information in an exceedingly component is created through editing function. With this, we have worked on Currency Format support in Web Client application and implemented a concept of Lazy Loading. Responsive web functionality improve server throughput that shows the response function of Web Client and therefore the processing speed is improved. All features can operate in real-time manners with our software architecture and loading mechanism, called Lazy Loading.

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Content Strategy in Management of Communications

Independent Journal of Management & Production ◽

10.14807/ijmp.v12i3.1538 ◽

2021 ◽

Vol 12 (3) ◽

pp. s232-s242

Author(s):

Olha Balabash ◽

Valerii Ilin ◽

Nataliia Poprozman ◽

Inna Kuznetsova ◽

Dmytro Shushpanov ◽

...

Keyword(s):

Real Estate ◽

Supply And Demand ◽

Real Estate Market ◽

The Real ◽

The Real Estate ◽

Construction Company ◽

The Real Estate Market ◽

Content Strategy ◽

Alternative Sources ◽

The Web

The aim of the article is to substantiate the theoretical and methodological support for the formation and implementation of the content strategy of a construction company. The article considers the formation of content strategy, its place in the management of communications of the enterprise. The following methods were used in the course of the research: the method of statistical analysis (for the analysis of the tendency of the real estate market development of Ukraine); analysis, synthesis, logical and theoretical generalization – to specify the factors of supply and demand in the real estate market; graphical method, table method (to visualize the results of the study); method of calculating specific indicators of communicative activity (CPC (Cost Per Click), CPA (Cost Per Action), CTR (Click Through Rate)) for analysing trends in traffic to the company's website and identifying alternative sources of traffic. The specifics of developing a content strategy taking into account the peculiarities of the company's construction industry are shown. An analysis of trends in the real estate market of Ukraine is carried out based on official statistics. The dynamics of the volume of construction works is analysed, the housing price indices in Ukraine are determined and the factors of supply and demand in the real estate market are specified. The analysis of communicative efficiency of the web-system of the construction company is carried out, as a result of which, measures for improvement of management of its external communications by substantiation of variants of advancement on the Internet are developed. This is done by analysing trends in traffic to the company's website and identifying alternative sources of traffic. The developed measures will increase the efficiency of management of the construction company. The article proposed a procedure for analysing the web-system of a construction company based on attendance indicators and search activity, which allows identifying alternative sources of traffic and developing appropriate measures to manage communications of the enterprise in order to achieve their efficiency. The practical significance lies in the fact that the developed recommendations for the formation of the communication strategy of the construction company can be further used to intensify the promotion of the company's services in the real estate market and attract investment.

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Predicting Days on Market to Optimize Real Estate Sales Strategy

Complexity ◽

10.1155/2020/4603190 ◽

2020 ◽

Vol 2020 ◽

pp. 1-22

Author(s):

Mauro Castelli ◽

Maria Dobreva ◽

Roberto Henriques ◽

Leonardo Vanneschi

Keyword(s):

Machine Learning ◽

Real Estate ◽

Real Estate Market ◽

Machine Learning Algorithms ◽

Lasso Regression ◽

The Real Estate ◽

Sales Strategy ◽

On Demand ◽

The Real Estate Market ◽

Real Estate Sales

Irregularities and frauds are frequent in the real estate market in Bulgaria due to the substantial lack of rigorous legislation. For instance, agencies frequently publish unreal or unavailable apartment listings for a cheap price, as a method to attract the attention of unaware potential new customers. For this reason, systems able to identify unreal listings and improve the transparency of listings authenticity and availability are much on demand. Recent research has highlighted that the number of days a published listing remains online can have a strong correlation with the probability of a listing being unreal. For this reason, building an accurate predictive model for the number of days a published listing will be online can be very helpful to accomplish the task of identifying fake listings. In this paper, we investigate the use of four different machine learning algorithms for this task: Lasso, Ridge, Elastic Net, and Artificial Neural Networks. The results, obtained on a vast dataset made available by the Bulgarian company Homeheed, show the appropriateness of Lasso regression.

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