• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.1-20
• /
• 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.

• Applied Biological Chemistry
• /
• v.21 no.3
• /
• pp.150-184
• /
• 1978

Nutritional characteristics and physio-chemical properties of mycelial growth and fruitbody formation of oyster mushroom(Pleurotus ostreatus)in synthetic media, the curtural condition for the commerical production in the rice straw and poplar sawdust media, and the changes of the chemical components of the media and mushroom during the cultivation were investigated. The results can be summarized as follows: 1. Among the carbon sources mannitol and sucrose gave rapid mycelial growth and rapid formation of fruit-body with higher yield, while lactose and rhamnose gave no mycelial growth. Also, citric acid, succinic acid, ethyl alcohol and glycerol gave poor fruit-body formation, and acetic acid, formic acid, fumaric acid, n-butyl alcohol, n-propyl alcohol and iso-butyl alcohol inhibited mycelial growth. 2. Among the nitrogen sources peptone gave rapid mycelial growth and rapid formation of fruit-body with higher yield, while D,L-alanine, asparatic acid, glycine and serine gave very poor fruit-body formation, and nitrite nitrogens, L-tryptophan and L-tyrosine inhibited mycelial growth. Inorganic nitrogens and amino acids added to peptone were effective for fruit-body growth, and thus addition of ammonium sulfate, ammonium tartarate, D,L-alanine and L-leucine resulted in about 10% increase fruit-body yield. L-asparic acid about 15%, L-arginine about 20%, L-glutamic acid, and L-lysine about 25%. 3. At C/N ratio of 15.23 fruit-body formation was fast, but the yield decreased, and at C/N ratio of 11.42 fruit-body formation was slow, but the yield increased. Also, at the same C/N ratio the higher the concentration of mannitol and petone, the higher yield was produced. Thus, from the view point of both yield of fruit-body and time required for fruiting the optimum C/N ratio would be 30. 46. 4. Thiamine, potassium dihydrogen phosphate and magnecium sulfate at the concentration of $50{\mu}g%$. 0.2% and 0.02-0.03%, respectively, gave excellent mycelial and fruit-body growth. Among the micronutrients ferrous sulfate, zinc sulfate and manganese sulfate showed synergetic growth promoting effect but lack of manganese resulted in a little reduction in mycelial and fruit-body growth. The optimum concentrati on of each these nutrients was 0.02mg%. 5. Cytosine and indole acetic acid at 0.2-1mg% and 0.01mg%, respectively, increased amount of mycelia, but had no effect on yield of fruit-body. The other purine and pyrimidine bases and plant hormones also had no effect on mycelial and fruit-belly yield. 6. Illumination inhibited mycelial growth, but illumination during the latter part of vegetative growth induced primordia formation. The optimum light intensity and exposure time was 100 to 500 lux and 6-12 hours per day, respectively. Higher intensity of light was injurous, and in darkness only vegetative growth without primordia formation was continued. 7. The optimum temperature for mycelial growth was $25^{\circ}C$ and for fruit-body formation 10 to $15^{\circi}C$. The optimum pH range was from 5.0 to 6.5. The most excellent fry it-body formation were produced from the mycelium grown for 7 to 10 days. The lesser the volume of media, the more rapid the formation of fruit-body; and the lower the yield of fruit-body; and the more the volume of media, the slower the formation of fruit-body, and the higher the yield of fruit-body. The primordia formation was inhibited by $CO_2$. 8. The optimum moisture content for mycelial growth was over 70% in the bottle media of rice straw and poplar sawdust. 10% addition of rice bran to the media exhibited excellent mycelial growth and fruit-body formation, and the addition of calciumcarbonate alone was effective, but the addition of calcium carbonate was ineffective in the presence of rice bran. 9. In the cultivation experiments the total yield of mushroom from the rice straw media was $14.99kg/m^2$, and from the sawdust media $6.52kg/m^2$, 90% of which was produced from the first and second cropping period. The total yield from the rice straw media was about 2.3 times as high as that from the sawdust media. 10. Among the chemical components of the media little change was observed in the content of ash on the dry weight basis, and organic matter content decreased as the cultivation progressed. Moisture content, which was about 79% at the time of spawning, decreased a little during the period of mycelial propagation, after which no change was observed. 11. During the period from spawning to the fourth cropping about 16.7% of the dry matter, about 19.3% of organic matter, and about 40% of nitrogen were lost from the rice straw media; about 7.5% of dry mallet, about 7.6% of organic matter, and about 20% of nitrogen were lost from the sawdust media. For the production of 1kg of mushroom about 232g of organic matter and about 7.0g of nitrogen were consumed from the rice straw media; about 235g of organic matter and about 6.8g of nitrogen were consumed from the sawdust media, 1㎏ of mushroom from either of media contains 82.4 and 82.3g of organic matter and 5.6 and 5.4g of nitrogen, respectively. 12. Total nitrogen content of the two media decreased gradually as the cultivation progressed, and total loss of insoluble nitrogen was greater than that of soluble nitrogen. Content of amino nitrogen continued to increase up to the third cropping time, after which it decreased. 13. In the rice straw media 28.0 and 13.8% of the total pentosan and ${\alpha}$-cellulose, respectively, lost during the whole cultivation period was lost during the period of mycelial growth; in the sawdust media 24.1 and 11.9% of the total pentosan and ${\alpha}$-cellulose, respectively, was lost during the period of mycelial growth. Lignin content in the media began to decrease slightly from the second cropping time, while the content of reduced sugar, trehalose and mannitol continued to increase. C/N ratio of the rice straw media decreased from 33.2 at spawining to 30.0 at ending; that of the sawdust media decreased from 61.3 to 60.0. 14. In both media phosphorus, potassium, manganese and zinc decreased, at magnesium, calcium and copper showed irregular changes, and iron had a tendency to be increased. 15. Enzyme activities are much higher in the rice straw media than in the sawdust media. CMC saccharifying and liquefying activity gradually increased from after mycelial propagation to the second cropping, after which it decreased in both media. Xylanase activity rapidly and greatly increased during the second cropping period rather than the first period. At the start of the third cropping period the activity decreased rapidly in the rice straw media, which was not observed in the sawdust media. Protease activity was highest after mycelial propagation, after which it gradually decreased. The pH of the rice straw media decreased from 6.3 at spawning to 5.0 after fourth cropping; that of the sawdust media decreased from 5.7 to 4.9. 16. The contents of all the components except crude fibre of the mushroom from the rice straw media were higher than those from the sawdust media. Little change was observed in the content of the components of mushroom cropped from the first to the third period, but slight decrease was noticed at the fourth cropping.