• Title/Summary/Keyword: Improvement Factor Limitation

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Improvement of Character-net via Detection of Conversation Participant (대화 참여자 결정을 통한 Character-net의 개선)

  • Kim, Won-Taek;Park, Seung-Bo;Jo, Geun-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.241-249
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    • 2009
  • Recently, a number of researches related to video annotation and representation have been proposed to analyze video for searching and abstraction. In this paper, we have presented a method to provide the picture elements of conversational participants in video and the enhanced representation of the characters using those elements, collectively called Character-net. Because conversational participants are decided as characters detected in a script holding time, the previous Character-net suffers serious limitation that some listeners could not be detected as the participants. The participants who complete the story in video are very important factor to understand the context of the conversation. The picture elements for detecting the conversational participants consist of six elements as follows: subtitle, scene, the order of appearance, characters' eyes, patterns, and lip motion. In this paper, we present how to use those elements for detecting conversational participants and how to improve the representation of the Character-net. We can detect the conversational participants accurately when the proposed elements combine together and satisfy the special conditions. The experimental evaluation shows that the proposed method brings significant advantages in terms of both improving the detection of the conversational participants and enhancing the representation of Character-net.

Frameless Fractionated Stereotactic Radiaton Therapy in Recurrent Head & Neck Cancers (국소재발된 두경부종양의 무고정틀 정위적 분할방사선치료)

  • Kim In-Ah;Choi Ihl-Bhong;Jang Ji-Young;Kang Ki-Mun;Jho Seung-Ho;Kim Hyung-Tae;Lee Kyung-Jin;Choi Chang-Rak
    • Korean Journal of Head & Neck Oncology
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    • v.14 no.2
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    • pp.156-163
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    • 1998
  • Background & Objectives: Frameless fractionated stereotactic radiotherapy(FFSRT) is a modification of stereotactic radiosurgery(SRS) with radiobiologic advantage of fractionation without losing mechanical accuracy of SRS. Local recurrence of head and neck cancer at or near skull base benefit from reirradiation. Main barrier to successful palliation is dose limitation secondary to normal tissue tolerance. We try to evaluate the efficacy and safety of FFSRT as a new modality of reirradaton in these challenging patients. Materials & Methods: Seven patients with recurrent head & neck cancer involving at or near skull base received FFSRT from September 1995 to November 1997. Six patients with nasopharyngeal cancer had received induction chemotherapy and curative radiation therapy. One patient with maxillary sinus cancer had received total maxillectomy and postoperative radiation therapy as a initial treatment. Follow-up ranged from 11 to 32 months with median of 24 months. Three of 7 patients received hyperfractionated radiation therapy(1.1-1.2Gy/fraction, bid, total 19.8-24Gy) just before FFSRT. All patients received FFSRT(3-5Gy/fraction, total 15-30Gy/5-10fractions). Chemotherapy(cis-platin $100mg/m^2$) were given concurrently with FFSRT in four patients. Second course of FFSRT were given in 4 patients with progression or recurrence after initial FFSRT. Because IF(irregularity factor; ratio of surface area of target to the surface area of sphere with same volume as a target) is too big to use conventional stereotactic RT using multiple arc method for protection of radiation damage to critical normal tissue, all patients received FFSRT with conformal method using irregular static ports. Results: Five of 7 patients showed complete remission in follow-up CT &/or MRI. Three of these five patients who developed marginal, in-field, and out-field recurrences, respectively. Another one of complete responders has been dead of G-I bleeding without evidence of local recurrence. One partial responder who showed progressive disease 15 months after initial FFSRT has received additional FFSRT, and then he is well-being with symptomatic improvement. One minmal responder who showed progression of locoregional disease 9 months after $1^{st}$ FFSRT has received 2nd FFSRT, and then he is alive with stable disease. Five of 7 case had showed direct invasion to skull base and had complaint headache and various symptoms of cranial nerve involvement. Four of these five case showed improvement of neurologic symptoms after FFSRT. No significant neurologic complicaltion related to FFSRT was observed during follow-up periods. Tumor volumes were ranged from 3.9 to 50.7 cc and surface area ranged from 16.1 to $114.9cm^2$. IF ranged from 1.21 to 1.74. The average ratio of volume of prescription isodose shell to target volume was 1.02 that indicated the improvement of target coverage and dose distribution with FFSRT with conformal method compared to target coverage with FFSRT with multiple arc method. Conclusion: Our initial experience suggests that FFSRT with conformal method was relatively effective and safe modality in the treatment of recurrent head and neck cancer involving at or near skull base. Treatment benefit included good palliation of symptoms and reasonable radiographic response. However, more experience and additional follow-up are needed to better assess its ultimate role in treating these challenging patients.

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A Study of Improvement for the Prediction of Groundwater Pollution in Rural Area: Application in Keumsan, Korea (농촌지역 지하수의 오염 예측 방법 개선방안 연구: 충남 금산 지역에의 적용)

  • Cheong, Beom-Keun;Chae, Gi-Tak;Koh, Dong-Chan;Ko, Kyung-Seok;Koo, Min-Ho
    • Journal of Soil and Groundwater Environment
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    • v.13 no.4
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    • pp.40-53
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    • 2008
  • Groundwater pollution prediction methods have been developed to plan the sustainable groundwater usage and protection from potential pollution in many countries. DRASTIC established by US EPA is the most widely used groundwater vulnerability mapping method. However, the DRASTIC showed limitation in predicting the groundwater contamination because the DRASTIC method is designed to embrace only hydrogeologic factors. Therefore, in this study, three different methods were applied to improve a groundwater pollution prediction method: US EPA DRASTIC, Modified-DRASTIC suggested by Panagopoulos et al. (2006), and LSDG (Land use, Soil drainage, Depth to water, Geology) proposed by Rupert (1999). The Modified-DRASTIC is the modified version of the DRASTIC in terms of the rating scales and the weighting coefficients. The rating scales of each factor were calculated by the statistical comparison of nitrate concentrations in each class using the Wilcoxon rank-sum test; while the weighting coefficients were modified by the statistical correlation of each parameter to nitrate concentrations using the Spearman's rho test. The LSDG is a simple rating method using four factors such as Land use, Soil drainage, Depth to water, and Geology. Classes in each factor are compared by the Wilcoxon rank-sum test which gives a different rating to each class if the nitrate concentration in the class is significantly different. A database of nitrate concentrations in groundwaters from 149 wells was built in Keumsan area. Application of three different methods for assessing the groundwater pollution potential resulted that the prediction which was represented by a correlation (r) between each index and nitrate was improved from the EPA DRASTIC (r = 0.058) to the modified rating (r = 0.245), to the modified rating and weights (r = 0.400), and to the LSDG (r = 0.415), respectively. The LSDG seemed appropriate to predict the groundwater pollution in that it contained land use as a factor of the groundwater pollution sources and the rating of each class was defined by a real pollution nitrate concentration.

New Approaches for Overcoming Current Issues of Plasma Sputtering Process During Organic-electronics Device Fabrication: Plasma Damage Free and Room Temperature Process for High Quality Metal Oxide Thin Film

  • Hong, Mun-Pyo
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.100-101
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    • 2012
  • The plasma damage free and room temperature processedthin film deposition technology is essential for realization of various next generation organic microelectronic devices such as flexible AMOLED display, flexible OLED lighting, and organic photovoltaic cells because characteristics of fragile organic materials in the plasma process and low glass transition temperatures (Tg) of polymer substrate. In case of directly deposition of metal oxide thin films (including transparent conductive oxide (TCO) and amorphous oxide semiconductor (AOS)) on the organic layers, plasma damages against to the organic materials is fatal. This damage is believed to be originated mainly from high energy energetic particles during the sputtering process such as negative oxygen ions, reflected neutrals by reflection of plasma background gas at the target surface, sputtered atoms, bulk plasma ions, and secondary electrons. To solve this problem, we developed the NBAS (Neutral Beam Assisted Sputtering) process as a plasma damage free and room temperature processed sputtering technology. As a result, electro-optical properties of NBAS processed ITO thin film showed resistivity of $4.0{\times}10^{-4}{\Omega}{\cdot}m$ and high transmittance (>90% at 550 nm) with nano- crystalline structure at room temperature process. Furthermore, in the experiment result of directly deposition of TCO top anode on the inverted structure OLED cell, it is verified that NBAS TCO deposition process does not damages to the underlying organic layers. In case of deposition of transparent conductive oxide (TCO) thin film on the plastic polymer substrate, the room temperature processed sputtering coating of high quality TCO thin film is required. During the sputtering process with higher density plasma, the energetic particles contribute self supplying of activation & crystallization energy without any additional heating and post-annealing and forminga high quality TCO thin film. However, negative oxygen ions which generated from sputteringtarget surface by electron attachment are accelerated to high energy by induced cathode self-bias. Thus the high energy negative oxygen ions can lead to critical physical bombardment damages to forming oxide thin film and this effect does not recover in room temperature process without post thermal annealing. To salve the inherent limitation of plasma sputtering, we have been developed the Magnetic Field Shielded Sputtering (MFSS) process as the high quality oxide thin film deposition process at room temperature. The MFSS process is effectively eliminate or suppress the negative oxygen ions bombardment damage by the plasma limiter which composed permanent magnet array. As a result, electro-optical properties of MFSS processed ITO thin film (resistivity $3.9{\times}10^{-4}{\Omega}{\cdot}cm$, transmittance 95% at 550 nm) have approachedthose of a high temperature DC magnetron sputtering (DMS) ITO thin film were. Also, AOS (a-IGZO) TFTs fabricated by MFSS process without higher temperature post annealing showed very comparable electrical performance with those by DMS process with $400^{\circ}C$ post annealing. They are important to note that the bombardment of a negative oxygen ion which is accelerated by dc self-bias during rf sputtering could degrade the electrical performance of ITO electrodes and a-IGZO TFTs. Finally, we found that reduction of damage from the high energy negative oxygen ions bombardment drives improvement of crystalline structure in the ITO thin film and suppression of the sub-gab states in a-IGZO semiconductor thin film. For realization of organic flexible electronic devices based on plastic substrates, gas barrier coatings are required to prevent the permeation of water and oxygen because organic materials are highly susceptible to water and oxygen. In particular, high efficiency flexible AMOLEDs needs an extremely low water vapor transition rate (WVTR) of $1{\times}10^{-6}gm^{-2}day^{-1}$. The key factor in high quality inorganic gas barrier formation for achieving the very low WVTR required (under ${\sim}10^{-6}gm^{-2}day^{-1}$) is the suppression of nano-sized defect sites and gas diffusion pathways among the grain boundaries. For formation of high quality single inorganic gas barrier layer, we developed high density nano-structured Al2O3 single gas barrier layer usinga NBAS process. The NBAS process can continuously change crystalline structures from an amorphous phase to a nano- crystalline phase with various grain sizes in a single inorganic thin film. As a result, the water vapor transmission rates (WVTR) of the NBAS processed $Al_2O_3$ gas barrier film have improved order of magnitude compared with that of conventional $Al_2O_3$ layers made by the RF magnetron sputteringprocess under the same sputtering conditions; the WVTR of the NBAS processed $Al_2O_3$ gas barrier film was about $5{\times}10^{-6}g/m^2/day$ by just single layer.

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The Effects of Perceived Quality Factors on the Customer Loyalty: Focused on the Analysis of Difference between PB and NB (지각된 품질요인이 고객충성도에 미치는 영향: PB와 NB간의 차이분석)

  • Ye, Jong-Suk;Jun, So-Yon
    • Journal of Distribution Research
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    • v.15 no.2
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    • pp.1-34
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    • 2010
  • Introduction As consumers' purchase behavior change into a rational and practical direction, the discount store industry came to have keen competition along with rapid external growth. Therefore as a solution, distribution businesses are concentrating on developing PB(Private Brand) which can realize differentiation and profitability at the same time. And as improvement in customer loyalty beyond customer satisfaction is effective in surviving in an environment with keen competition, PB is being used as a strategic tool to improve customer loyalty. To improve loyalty among PB users, it is necessary to develop PB by examining properties of a customer group, first of all, quality level perceived by consumers should be met to obtain customer satisfaction and customer trust and consequently induce customer loyalty. To provide results of systematic analysis on relations between antecedents influenced perceived quality and variables affecting customer loyalty, this study proposed a research model based on causal relations verified in prior researches and set 16 hypotheses about relations among 9 theoretical variables. Data was collected from 400 adult customers residing in Seoul and the Metropolitan area and using large scale discount stores, among them, 375 copies were analyzed using SPSS 15.0 and Amos 7.0. The findings of the present study followed as; We ascertained that the higher company reputation, brand reputation, product experience and brand familiarity, the higher perceived quality. The study also examined the higher perceived quality, the higher customer satisfaction, customer trust and customer loyalty. The findings showed that the higher customer satisfaction and customer trust, the higher customer loyalty. As for moderating effects between PB and NB in terms of influences of perceived quality factors on perceived quality, we can ascertain that PB was higher than NB in the influences of company reputation on perceived quality while NB was higher than PB in the influences of brand reputation and brand familiarity on perceived quality. These results of empirical analysis will be useful for those concerned to do marketing activities based on a clearer understanding of antecedents and consecutive factors influenced perceived quality. At last, discussions about academical and managerial implications in these results, we suggested the limitations of this study and the future research directions. Research Model and Hypotheses Test After analyzing if antecedent variables having influence on perceived quality shows any difference between PB and NB in terms of their influences on them, the relation between variables that have influence on customer loyalty was determined as Figure 1. We established 16 hypotheses to test and hypotheses are as follows; H1-1: Perceived price has a positive effect on perceived quality. H1-2: It is expected that PB and NB would have different influence in terms of perceived price on perceived quality. H2-1: Company reputation has a positive effect on perceived quality. H2-2: It is expected that PB and NB would have different influence in terms of company reputation on perceived quality. H3-1: Brand reputation has a positive effect on perceived quality. H3-2: It is expected that PB and NB would have different influence in terms of brand reputation on perceived quality. H4-1: Product experience has a positive effect on perceived quality. H4-2: It is expected that PB and NB would have different influence in terms of product experience on perceived quality. H5-1: Brand familiarity has a positive effect on perceived quality. H5-2: It is expected that PB and NB would have different influence in terms of brand familiarity on perceived quality. H6: Perceived quality has a positive effect on customer satisfaction. H7: Perceived quality has a positive effect on customer trust. H8: Perceived quality has a positive effect on customer loyalty. H9: Customer satisfaction has a positive effect on customer trust. H10: Customer satisfaction has a positive effect on customer loyalty. H11: Customer trust has a positive effect on customer loyalty. Results from analyzing main effects of research model is shown as

    , and moderating effects is shown as
    . Results This study is designed with 16 research hypotheses, Results from analyzing their main effects show that 9 of 11 hypotheses were supported and other 2 hypotheses were rejected. On the other hand, results from analyzing their moderating effects show that 3 of 5 hypotheses were supported and other 2 hypotheses were rejected. H1-1: (SPC: Standardized Path Coefficient)=-0.04, t-value=-1.04, p>. 05). H1-2: (${\Delta}\chi^2$=1.10, df=1, p> 0.05). H1-1 and H1-2 are rejected, so it is prove that perceived price is not a significant decision variable having influence on perceived quality and there is no significant variable between PB and NB in terms of influence of perceived price on perceived quality. H2-1: (SPC=0.31, t-value=3.74, p<. 001). H2-2: (${\Delta}\chi^2$=3.93, df=1, p< 0.05). H2-1 and H2-2 are supported, so it is proved that company reputation is a significant decision variable having influence on perceived quality and, in terms of influence of company reputation on perceived quality, PB has relatively stronger influence than NB. H3-1: (SPC=0.26, t-value=5.30, p< .001). H3-2: (${\Delta}\chi^2$=16.81, df=1, p< 0.01). H3-1 and H3-2 are supported, so it is proved that brand reputation is a significant decision variable having influence on perceived quality and, in terms of influence of brand reputation on perceived quality, NB has relatively stronger influence than PB. H4-1: (SPC=0.31, t-value=2.65, p< .05). H4-2: (${\Delta}\chi^2$=1.26, df=1, p> 0.05). H4-1 is supported, but H4-2 is rejected, Therefore, it is proved that product experience is a significant decision variable having influence on perceived quality and, on the other hand, there is no significant different between PB and NB in terms of influence of product experience on product quality. H5-1: (SPC=0.24, t-value=3.00, p<. 05). H5-2: (${\Delta}\chi^2$=5.10, df=1, p< 0.05). H5-1 and H5-2 are supported, so it is proved that brand familiarity is a significant decision variable having influence on perceived quality and, in terms of influence of brand familiarity on perceived quality, NB has relatively stronger influence than PB. H6: (SPC=0.91, t-value=19.06, p< .001). H6 is supported, so a fact that customer satisfaction increases as perceived quality increases is proved. H7: (SPC=0.81, t-value=7.44, p<. 001). H7 is supported, so a fact that customer trust increases as perceived quality increases is proved. H8: (SPC=0.57, t-value=7.87, p< .001). H8 is supported, so a fact that customer loyalty increases as perceived quality increases is proved. H9: (SPC=0.08, t-value=0.76, p> .05). H9 is rejected, so it is proved influence of customer satisfaction on customer trust is not significant. H10: (SPC=0.21, t-value=4.34, p< .001). H10 is supported, so a fact that customer loyalty increases as customer satisfaction increases is proved. H11: (SPC=0.40, t-value=5.68, p< .001). H11 is supported, so a fact that customer loyalty increases as customer trust increases is proved. Implications Although most of existing studies have used function, price, brand, design, service, brand name, store name as antecedent variables for perceived quality, this study used different antecedent variables in order to analyze and distinguish purchase group PB and NB through preliminary research. Therefore, this study may be used as preliminary data for a empirical study that is designed to be helpful for practical jobs. Also, this study is made to be easily applied to any practical job because SEM(Structural Equation Modeling), most strongly explaining the relation between observed variable and latent variable, is used for this study. This study suggests a new strategic point that, in order to increase customer loyalty, customer's perceived quality level should satisfied for inducing customer satisfaction, customer trust, and customer loyalty. Therefore, after finding an effective differentiating factors in perceived quality in order to increase customer loyalty through increasing perceived quality, this factor was made to be applied to PB and NB. Because perceived quality factors which is recognized as being important by consumers is different between PB and NB, this study suggests how to efficiently establish marketing strategy by enhancing a factor. Companies have mostly focused on profitability in terms of analyzing customer loyalty, but this study included positive WOM(word of mouth). Hence, this study suggests that it would be helpful for establishing customer loyalty when consumers have cognitive satisfaction and emotional satisfaction together. Limitations This study used variables perceived price, company reputation, brand reputation, product experience, brand familiarity in order to determine whether each constituent factor has different influence on perceived quality between purchase group PB and NB. These characteristic variables are made up on the basis of the preliminary research, but it is expected that more precise research result would be obtained if additional various variables are included in study. This study selected a practical product that is non-durable, low-priced and bestselling product in a discount store through the preliminary research because it can be easily estimated by consumers. Therefore. generalization of study would be more easily obtained if more various product characteristics is included. Regarding a sample used in this study, it was only based on consumers who purchase products in a large-scale discount store located in Seoul and in the capital area. Accordingly, this sample has some geographical limitation, If a study is expanded by including more areas, more representative research results may be produced. Because this study is only designed to analyze consumers who purchase a product in a large-scale discount store, some difference may be found according to characteristics of each business type. In other words, there is certainly some application limitation, so research result from this study may not be applied to other business types. Future research may have fruitful results if it adjusts a variable to each business type.

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  • Incorporating Social Relationship discovered from User's Behavior into Collaborative Filtering (사용자 행동 기반의 사회적 관계를 결합한 사용자 협업적 여과 방법)

    • Thay, Setha;Ha, Inay;Jo, Geun-Sik
      • Journal of Intelligence and Information Systems
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      • v.19 no.2
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      • pp.1-20
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      • 2013
    • Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.


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