• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

• Korean Security Journal
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• no.33
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• pp.103-135
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• 2012

The object is that this research searches the relationship of the office given condition actual condition of the country important facility private security guard and job satisfaction degree. In order to grasp and analyze the real state of the country important facility private security guards directly, the questionnaire, that is the general measurement tool, was utilized and the guard whom it works in the airport, the port region and general work place, that is the national important facility of Busan and Ulsan area, was aimed at. The enough survey object was illustrated to the facility and person in charge in the security company and the item was previewed and the total 400 sheets was distributed and 331 sheets (82.8%) except the doubleness subject intention and incongruent questionnaire was utilized for the analysis. The statistic processing of collected data utilized the SPSS version 15.0 the statistical package program through data coding and cleaning process and performed the frequency analysis, reliability analysis, t-test, one way analysis of variance, Pearson analysis, and regression analysis. The relationship of the office given condition actual condition of the guard about the national important facility and job satisfaction degree was classified into the interpersonal relationship, task characteristic, office environment, and complement factor and the difference of the job satisfaction degree according to the general characteristic was verified. If the conclusion obtained through the method of study described in the above looked at, for as to general tendency, the low wages and poor field environment was continued. In the general characteristic, the man was higher than the excitation about the job satisfaction level. As there was lots of the age and the scholarship was low, the age was high. And as there was lots of the career and income, the police of a petition or search and guide staff was high and the job satisfaction degree in which relatively the employee and the other job group is high so that the case of being the former student incidence can be the poorest was shown rather than the facility security agent. As the interrelation analysis result job satisfaction was high, the change of occupation pseudo was low and the organizational commitment degrees was increased. The regression analysis result job satisfaction degree was exposed to reach the meaningful effect on the change of occupation pseudo and organizational commitment. It had an effect on the change of occupation pseudo as the task characteristic and office ambient level was low. It had an effect on the organizational commitment as the extend of satisfaction about the task characteristic and interpersonal relationship, complement, and office ambient level were high. If the research result of this time is integrated, the support of the political system including the interpersonal relationship thesis between top and bottom of the organized I and substantial complement actualization is urgently needed between the office given condition improvement effort in the country important facility defense manpower field and police of a petition and special guard.

• Clinical and Experimental Pediatrics
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• v.45 no.7
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• pp.855-861
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• 2002

Purpose : Thymus size can be affected by several factors and perinatal diseases can be estimated by its size. The purpose of this study was to search for a relationship between cardiothymic/thoracic(CT/T) ratio and perinatal diseases such as neonatal respiratory distress syndrome(RDS) and intrauterine growth retardation(IUGR) by measuring the width of the cardiothymic shadow at the level of the carina and dividing it by the width of the thorax at the costophrenic angles. Methods : A clinical study was conducted on newborn infants with RDS(n=51), IUGR(n=27), and premature rupture of membranes(PROM, n=48), who were admitted at NICU of Catholic University of Daegu from June 2000 to Oct. 2001. CT/T ratio was measured within six hrs of age, at 2-3 days of age, and at 5-7 days of age. Results : CT/T ratios of RDS group, IUGR group, and PROM group were $0.46{\pm}0.07$, $0.32{\pm}0.04$. $0.36{\pm}0.06$, respectively. CT/T ratios of RDS group within 6hrs of age, at 2-3 days of age, and at 5-7 days of age were $0.43{\pm}0.07$, $0.34{\pm}0.06$, $0.25{\pm}0.04$, respectively. There were statistically significances among the RDS group, the IUGR group, and the PROM group and in the RDS group at different times. Regression for gestational age among three groups was not statistically significant but correlation for gestational age in the entire groups was statistically significant. CT/T ratio between normal spontaneous vaginal delivery and c-section among three groups was not statistically significant. CT/T ratios with dexamethasone-treated group and untreated group was not statistically significant. Conclusion : We concluded that thymus size differed significantly in the perinatal diseases such as RDS and IUGR, and so can be used as an early diagnostic tool for perinatal diseases.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.3
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• pp.480-486
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• 2004

Despite many therapeutic advances in the understanding of the processes in carcinogenesis, overall mortality statistics are unlikely to change until there is reorientation of the concepts for the use of natural products as new anticarcinogenic agents. In this study, we investigated the anticarcinogenic activity, antioxidant and DPPH scavenging activity of Sargassum fulvellum (SF). SF was extracted with methanol, which was further fractionated into five different types: hexane (SFMH), ethylether (SFMEE), ethyl acetate (SFMEA), butanol (SFMB) and aqueous (SFMA) partition layers. We determined the cytotoxic effect of these layers on human cancer cells by MTT assay. Among various partition layers of SF, at starting concentration of 100 $\mu\textrm{g}$/mL, SFMEE showed very high cytotoxicity which were 92, 90 and 84% and kept high throughout 5 concentration levels sparsed by 100 $\mu\textrm{g}$/mL against all three human cancer cell lines: HepG2, HT-29 and HeLa. SFMEA showed a low cytotoxicity at the beginning concentration level, but as the concentration became denser, growth inhibition effect of cancer cell lines started to increase and at 500 $\mu\textrm{g}$/mL, it hit the highest, which were 91, 96 and 98% against the same three cell lines as above. We observed QR induced effect in all fraction layers of SF. SFMEE showed similar tendensy of QR induced effect as did against cytotoxicity. The QR induced effect of SFMEE on HepG2 cells at 25 $\mu\textrm{g}$/mL concentration indicated 3 times higher than the control value of 1.0 and SFMH tended to be concentration-dependent on HepG2 cells. At 100 $\mu\textrm{g}$/mL, the QR induced effects resulted a ratio, which was 2.5 times higher than the control value. In search for antioxidation effects of SF extract and partition layer, the reducing activity on the 1, 1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging potential was sequentially screened. The SFM has similar antioxidant activity as to BHT and vitamin C groups.

• Tuberculosis and Respiratory Diseases
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• v.43 no.4
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• pp.613-622
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• 1996

Constrictive bronchiolitis, one of small airway diseases, is very rare and occupies one of the two arms of bronchiolitis obliterans together with proliferative bronchiolitis. Proliferative bronchiolitis, presenting the prototype with bronchiolitis obliterans with organizing pneumonia(BOOP), can be easily taken into diagnostic consideration in terms of relatively rapid clinical course and radiologic presentation as if atypical pneumonia with interstitial and alveolar infiltrations. Meanwhile constrictive bronchiolitis is not only very Tare but also easily overlooked as chronic obstructive pulmonary diseases such as emphysema, because it usually shows normal chest radiographic finding and obstructive pattern in pulmonary function test. In the aspects of the response to treatment, proliferative bronchiolitis showed dramatic response to the corticosteroid while constrictive bronchiolitis is intractable, which is easily explained on the basis of the pathologic characteristics of cicartrical replacement of bronchiolar walls. The bronchiolitis, both proliferative and constrictive, can be associated with diverse conditions such as inhalational injury, postinfectious process, drug of chemical induced reactions, connective tissue diseases, and organ trasplantation. And there is idiopathic type which has no associated condition. There is one explanation that both types of bronchiolitis lie on the same disease spectrum because the different disease pattern can be evoked from the same etiology. In contrast, another explanation is suggested that both types of bronchiolitis are one of nonspecific tissue reaction rather than a disease specific histologic finding because the various types of causes can provoke the same histologic findings. These dilemma remains for further investigation. With literature investigation, the authors report a case of constrictive bronchiolitis proven by open lung biopsy in 47 year old female who was diagnosed as non-Hodgkin's lymphoma and simultaneously had relatively rapid progression of airflow obstruction and showed negative radiographic finding without the rise factors for the development of chronic obstructive lung disease. We consider it as idiopathic because we could not find any relationship between constrictive bronchiolitis and non-Hodgkin's lymphoma on the literature search and it requires further investigation.