3 research outputs found

    Time Based Collaborative Recommendation System by using Data Mining Techniques

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    Recommendation of appropriate product to the specific user is becoming the key to ensuring the continued success of E-commerce. Today, many E-commerce systems adopt various recommendation techniques, e.g., Collaborative Filtering (abbreviated as CF)-based technique and Structural Balance Theory-based Recommendation (i.e., SBT-Rec) technique to realize product item recommendation. Overall, the present CF recommendation and as per suggested SBT can perform very well, if the target user owns similar friends (user-based CF) and Structural Balance Theory-based Recommendation (i.e., SBT-Rec) for we first look for the target user’s dissimilar “enemy” (i.e., antonym of “friend”), and furthermore, we look for the “possible friends” of E-commerce target user, according to “enemy’s enemy is a friend” rule of Structural Balance Theory or the product items purchased and preferred by target user own one or more similar product items (item-based CF). Here both the systems depends on friends and enemies if we are not getting friends or enemies then. So to improve Recommender system we propose a time-aware profile based collaborative Recommendation algorithm. In this algorithm, we will consider only recently submitted ratings and positive reviews to evaluate products quality. Along with this, we propose a novel recommender system in which user will give his requirement about any product as input, and depending on that input we will recommend most appropriate products according to the customer’s requirement and ratings given by other customers. Only recent ratings will be considered by the system. Our proposed system will meet personalized product item recommendation requirements in E-commerce and time-aware rating consideration to evaluate current product quality

    The structure and dynamics of scholarly networks between the Dutch Republic and Grand Duchy of Tuscany in the 17th century

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    In recent years, the theoretical approaches of social network analysis have already made an impact in the historical field. Specifically, the Republic of Letters, the pan-European intellectual community of the sixteenth, seventeenth and eighteenth century, has been the subject of a rich interdisciplinary historiography for the past few decades. But although this letter-writing community has attracted more and more scholarly attention in conjunction with a global turn in the practice of the digital humanities, the study of networks in historical research remains a field in its infancy. It has yet to establish its methodology, its ontologies, the best digital tools, and even the language by which we invoke technical processes in the study of early modern history. Rarely do historical studies offer an actual implementation and testing of how the mathematical tools employed by network scientists offer valuable ways of understanding and exploring the past. Most studies underline the potential utility of network metrics, but leave their exploration for future research. To add to this conceptual murkiness, the use of digital tools is often looked upon in a suspicious way, considered to be too simplistic and hence unsuitable to deal with the complexity and uncertainty of historical sources. There is, as underlined by Ruth Ahnert and Sebastian Ahnert, \u201cstill much work to be done before statistical methods are embedded within the literary historian\u2019s toolbox\u201d. We need, therefore, to continue to sharpen our digital tools and experiment with network models that give nuance, subtilty and detail to historical data. This study attempts to take up this challenge and to demonstrate how social network analysis enables us to advance the cause of historical inquiry. It will address this challenge by exploring the ways in which early modern scholars capitalized on opportunities in the social structure to which they were connected. Accordingly, much of the essence of this study focuses on methodology rather than historical narrative. We might even say that this study has an experimental character in nature. Specifically, we will take a look at how early modern networks were actively and consciously constructed, modified, questioned and navigated by early modern scholars. They were constantly monitoring their interactions with one another in making decisions. On the one hand, early modern scholars were expected to contribute towards the achievement of the collective goals of the Republic of Letters \u2013 the bonum commune \u2013 that rested on the imperative of sharing knowledge without frontiers. Nevertheless, they had to deal with many tensions and inefficiencies at a time in which the freedom of communication was not always guaranteed. These tensions ranged from restrictions imposed by the Inquisition to scholarly rivalries, jealousy and competition. As a consequence, it seems that the citizens of the Republic of Letters often found themselves between extremes, struggling to find a balance in dealing with these tensions. They had to strategically negotiate between open and closed circles in their networks, between friendly and hostile relationships and between openness and secrecy in their communication. [...
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