• Journal of Popular Narrative
• /
• v.25 no.1
• /
• pp.165-191
• /
• 2019

The purpose of this article is to elucidate why the motif of time travel is repeated in the science fiction narrative by examining the functions of this motif in the SF movie series of Star Trek in its narrative and non-narrative aspects. Star Trek IV: The Voyage Home (1986) aims to attract the audience's interest in the story through the use of plausible time travel in the form of the slingshot effect which causes the spacecraft to fly at very fast speeds around an astronomical object. The movie also touches upon the predestination paradox that arises from a change of history in which it describes a formula of transparent aluminum that did not exist at the time. The film also serves as an evocation of the ideology of ecology by including humpback whales in the central narrative and responding to the real issue of the whale protection movement of the times. Star Track VIII: First Contact (1996) intends to interest the audience in the narrative with the warp drive, a virtual device that enables travel at speeds faster than that of light and a signature visual of Star Trek, at the time of its birth through time travel. The film emphasizes the continuation of peaceful efforts by warning the destruction of humanity that nuclear war can bring. It tackles with the view of pacifism and idealism by stressing the importance of cooperation between countries in the real world by making the audience anticipate the creation of the United Federation of Planets through encounters with the extraterrestrial. Star Trek: The Beginning (2009) improves interest through the idea of time travel to the past, this time using a black hole and the parallel universe created thereby. The parallel universe functions as a reboot, allowing a new story to be created on an alternate timeline while maintaining the original storyline. In addition, this film repeats the themes pacifism and idealism shown in the 1996 film through the confrontation between Spock (and the Starfleet) and Nero, the destruction of the Vulcan and the Romulus, and the cooperation of humans and Vulcans. Eventually, time travel in three Star Trek films has the function of maximizing the audience's interest in the story and allowing it to develop freely as a narrative tool. It also functions as an ideal solution for commenting on current problems in the non-narrative aspect. The significance of this paper is to stress the possibility that the motif of time travel in SF narrative will evolve as it continues to repeat in different forms as mentioned above.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.27-42
• /
• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.