The Georss Model Together with the Design of a Ranking Algorithm in Semantic Web

International Journal of Pure and Applied Mathematics Volume 120 No. 6 2018, 2895-2908 ISSN: 1314-3395 (on-line version) url: http://www.acadpubl.eu/hub/ Special Issue http://www.acadpubl.eu/hub/

THE GEORSS MODEL TOGETHER WITH THE DESIGN OF A RANKING ALGORITHM IN SEMANTIC WEB

1 2 A.Bennani∗ , S.Bourekkadi , S.Khoulji1, M.L.Kerkeb1 1ISER, Information Systems Engineering Research Group Abdelmalek Essaadi University, Tetouan, Morocco 2LRMO national school of commerce and management, Ibn Tofail University , Morocco *orcid.org/0000-0002-9684-1001 July 9, 2018

Abstract These days E-commerce has proven to be an powerful character in the international trade business and has vastly led to the econom-ic growth of countries. The reality of working with this speciality alongside the growth of innovations renders the e-commerce more utilizable by web surfers. The semantic web gives further technical results depending on the construction and arrangement of the current information on the web. In the midst of this Paper, I will address the issue of e-commerce in connection to geolocation, meanwhile i will be similarly giving the web surfer more liberty to notice the summit of the geographical region where he/she is situated by a suggesting an up to date geographical coordinate grouping algorithm. Keywords: E-commerce, semantic web, Algorithm for Ranking, GEORSS model, geo owl, OGC, FOAF ontology, GOODRELATIONS, geographic information.

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1 Introduction

E-commerce is interpreted as the selling or distribution of products and services by information systems and proce-dures specially made for admitting or placing orders. This definition was offered by the World Trade Organization (WTO); an international body that handles the regulations of trade within various nations. Internet commerce has turned out to be essential for a few nations of in the planet. French shoppers expended 72 billion euros online in 2016, which is a rise of 14.6 percent prior to the circumstance in the 2015. They processed 103 billion online exchanges, similar to 33 orders per second, developing by 23% , as indicated by the information posted of recent on Thursday 26 January by the French federation of E-commerce and Distance Selling (FE-VAD). To finalize the purchasing/selling procedure online, every one of the processes, from the item’s exposure to its payment, have to be checked in an effectual and safe way. Items have to be thoroughly specified. What’s more, their reported prices and the after-sales service have to be thoroughly-analysed. For whatever length of time that the items are properly pre-sented on the organization entryway, they will turn out to be clearly recognizable to any customer searching for them. The technology which permits the organizing of information via the internet and a suitable association is the semantic web. In this point of view, Tim Berners Lee has showed his plan by expressing the accompanying: ”Developing a web of information that may be directly and indirectly handled by the machines in order to help their clients to develop new knowledge [1] ”. In order to develop information in the semantic web, we for the most part use an ontology [2]. It is a formulation of an idea. Concerning our Semantic Web region, the World Wide Web Consortium (W3C) has explained ontology via An ontology is a formal specification of a typical set of terms used to depict and represent an area. It defines the terms used to describe and represent an area of knowledge”. [3] Similarly, the current paper will be bothered with the geo-graphic information System (GIS) that has turned out to be a integral piece of our day to day lives. Furthermore, this paper will specifically make usage of the GIS found in the Good-Relations

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ontology: e-commerce ontology. The GIS is uti-lized, as a tool, to state the area of a new shop or a speciﬁc store for an organization or a seller. Moreover, the develop-ment and utilization of (GIS) were revealed by the execution of the Web-based devices. The utilization of geographic information has vastly multiplied; nevertheless, numerous users will be greatly absent to the part it plays in their actions. This is due to the fact that GIS per se is taken as a genuinely scarce target; preferably, it ordinarily develops the outline under which the theme of interest is remarkable. [4] The fundamental objective of the current paper is to bring up an up to date method of utilizing GoodRelations with the GEORSS model. The later permits the portrayal of geo-graphic information on the semantic web. The reasoning underneath picking this procedure I will examine all through the current paper is to give anybody or visitor the likelihood to come up with a distance over which he/she may have data concerning the shops or stores that encompass him/her. I propose that the proprietors or vendors have to know how to utilize the GoodRelations ontology to represent their items and, similarly, should ensure that their geographic coordi-nates are executed by means of the possessions entitled to the geolocation. The procedure I propose here assumes an essential part in the tourism business, speciﬁcally for the good of voyagers who need to tour around a metropolis without a map.

2 EXISTING RANKING METHODS

2.1 Spatial data model: GeoRSS The Geographically Encoded Objects for RSS feeds (GeoRSS) is a module approved by the World Wide Web Consortium (W3C). It acts as a reference vocabulary for the analysing of the geospatial possessions of Web resources. The accompanying outline demonstrates the UML modeling of GeoRSS. This paper will analyse the crate measuring property of the model and will bring up its usefulness [5]. The Geography Markup Language (GML) is an updated edition of the GeoRSS model. It is a XML sentence structure for

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Figure 1: An Extract of the GeoRSS model

encoding, controlling and swapping spatial information. This standard is created by the Open Geospatial Consortium (OGC) to make certain the interoperability of information, especially in the fields of Geographic Information Systems and Geomatics. Such kind of vocabulary, mainly (XML), ensures the various kinds of things which analyse spatial information, incorporating institutions, coordinate reference frameworks, geometries, topologies, hours, units of quantifi-cation and overall factors [6]. GML is a group of XML schemas that state an open exchange style for interchanging information and that allow the developing of certain models for specific areas, for example, citified management. This part comprises of the advantages and the added value of this product to the geo-area and its effect on e-commerce.

2.2 GoodRelations Ontology For E-commerce The GoodRelations ontology comprises of a inclusive group of processes designed for e-commerce, beginning from the explanation of items prior to payment. This language is built by including extra semantic codes via the Web content [7]. Currently, the matter of e-commerce with the geographic area of shops shall be dealt with. The accompanying delineation [7]

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Figure 2: The box-sizing property of the GeoRSS model

technically demonstrates the possessions of the gr:location class.

Figure 3: The GoodRelations Location Class

The aim is to come up with a new method that could enable someone to pick a location that will allow someone to deter-mine the geographical zone in which one is situated. The aspired location directly aﬀects the surface zone, i.e., if the distance is immense, the surface zone will likewise be big. Eventually, because of the GoodRelations ontology, one can be familiar with the varying shops situated in the region and in addition their features and some data concerning the items that are for sale.

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2.3 Friend of a Friend (FOAF) Ontol-ogy For Person Friend Of a Friend (FOAF) is a generally used ontology in the semantic web that permits to analyse individuals by giv-ing all the necessary information on them, for example, their Websites, last names and names, etc. Also, this language gives the likelihood to understand the connections they have amongst each other[8]. In this analysis, the ontology will have data regarding the individuals who may become clients. In this manner, the shop proprietors who are situated in the established geo-graphical region can utilize that data to connect those indi-vidual’s attention. As a perfect example, ”a person loves eating chocolate”: such information is semantically registered in the ontology code. Meaning that, if a store, for example, is selling chocolate bars, that individual will be consequently informed about the oﬀer.

3 The Spatial Datum in the Semantic Web

3.1 Determination of GPS Coordi-nates So as to bring significance to the geographical area of a spe-cific individual, I propose an method that will enhance the recognition of the geographical region. At this point, we can utilize the GeoRSS model that we have demonstrated in the chapter stated above below the property “Box”. The pro-posed scenario is as follows: The individual who may want to be a client with a shop is located in a region stated by the geographic grid line and longitude coordinates (Lat1& Lon1). These variable consti-tute the main coordinates “lower corner” of the Box. The value added of this product is outlined as follows: to develop the geographic coordinates (Lat2 and Lon 2) of the “upper Corner” of the Box, you could decide the interval at which one might be enclosed by the rectangle tracked by the pos-session Box, with a bearing equal to 45 ◦ = Pi/4 Radians. Ordinarily, on the off chance that we are to identify the geo-graphic coordinates of a specific location, we

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should learn the coordinates of the retiral, of the interval completed and of the positioning angle. Because its variables are realized, we establish use of the formula built by Thaddeus Vincenty [9] to discover those coordinates accompanying an ellipsoidal model of the planet. Lat2 = ASIN(SIN(lat1)*COS(d/R) + COS(lat1)*SIN(d/R)*COS(Orient)) Lon2 = lon1 + ATAN2(COS(d/R)-SIN(lat1)*SIN(lat2) , SIN(Orient)*SIN(d/R)*COS(lat1)) Understanding that R: Ray of the Earth = 6371 Km; d = distance in Kilometers (Km); Orient = Orientation in radians.

Figure 4: Setup of the Property Box

The GeoRSS - Primary model takes advantage of the World Geodetic System (WGS84). Geodesy, in this case, is a coor-dinate framework utilized to specify the orientation correlat-ing to the minimal interval in the middle of two reference focuses on the ground. With regards to the sphere, it is the circular segment of a big circle. For example, by compre-hending the situation of two points presented in A and B on a spheroid, we could, however, to

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come up with the interval linking them, determine the curvilinear abscissa S (AB) on the big circle going between A and B, as it is presented in the accompanying figure. Geodesy is the science that examines this planet’s geometric figure, aspects and gravity field. Its principle aim is to create terrestrial reference frameworks to which any georeferenced information user or developer can have entry across the intercessor network. The acquisition and execution of such reference frameworks comprise a necessary institutionalization device for the geo-graphic information specifically and the placing in general. However, the approximations of a globe-shaped model are precise to inside 0.3%. Vincenty’s formula is precise to in-side 0.5 mm or 0.000015’ based on the ellipsoid utilized. Be aware that the exactness of theWGS-84 model will be small-er as indicated by the Earth’s position, yet widely in the range of 0.003% [10].

Figure 5: The Position of Two Points on a “Geodesic” Sphere

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3.2 Algorithm Conditions for the Ranking of Geographic Datum The algorithm suggested for this product needs conditions at the company level. Actually, the creator of this project had a Geographic Coordinate Database which involved the shops-in order of merit of the district or the metropolis where he was situated. This begins with the latitude and, after, longi-tude coordinates. This project takes into account that those coordinates are put together semantically because of the GoodRelations ontology and are brought out in order of merit and saved in a table. For example:

To the extent of the programming language, the coordinates of the store 4 will be stored in a table as takes after: Latitude = Tab [3] [0] = 0.7673675 and Longitude = Tab [3] [1] = 0.0236259.

3.3 Algorithm

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3.4 The Positioning of stores in relation to a particular person Immediately the geographic coordinates of the recorded shops have relevance to the bottom of the Box by means of the algorithm, we could identify the interval in the middle of the store and the situation of the individual asking the infor-mation, and the bearing (Angle toward the North). Further-more, this is on account of the accompanying formulae: d = ACOS(SIN(lat1)*SIN(lat2)+COS(lat1)*COS(lat2)* COS(lon2-lon1))*R Orientation = ATAN 2(COS(lat1)*SIN(lat2)-SIN(lat1)* COS(lat2)* COS(lon2-lon1), SIN(lon2lon1)*COS(lat2))

Here takes after a mathematically similar formula which is, but, less vulnerable to er-rors of an adjusting nature as far the short intervals are taken into account: d = 2 asin(sqrt((sin((lat1 lat2)/2))2 + cos(lat1) cos(lat2) (sin((lon∗ 1 lon2)/2))2)) − ∗ ∗ − This kind of formulas are set for a spherical model of the Earth and consists, as a result, the approximations. [11]

4 Conclusion

In this study, I have, from one viewpoint, indicated atten-tiveness in e-commerce and its connection with the spatial aspect. The objective, as earlier stated, is to give web users, widely, the chance to direct the coveted search on the geo-graphical region where they are situated and to permit them to get however much information as could be expected. The reality of joining e-commerce with geolocation in an arranged manner provides to a better association of the in-formation. I have likewise presented, similarly, that e-commerce has turned out to be an extremely smart sector in view that it oﬀers all web users, who are presently linked to technology more now than ever, the likelihood to conse-quently do any advanced proﬁt-oriented operation with the least number of intercessions. The outcome stated in this research will have a hand in the

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evolution of the traveler and economic sectors of the nations because it permits individuals in general and vacationers speciﬁcally to recognize the stores surrounding them and understand the kinds of their products given for sale from research. This study additionally eases the selling/buying procedure either at the seller level by picking out purchasers who show concern for their items, or apart from the pur-chaser who sees the wanted items that he will be able to buy them in no time. In the future work, our team will try to make a development of an information system able to sensitize the Net surfers to exercise the electronic commerce ensuring more security. We will also adapt our system by a very intellegent level of communication. Also we will improve our algorithm to put it more interactive

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