IMPROVING THE INTERESTINGNESS OF WEB USAGE MINING

Improvement on mining the frequently visited groups of web pages was studied. First, in the data preprocessing phrase, we introduce an extra frame filtering step that reduces the negative influence of frame pages on the result page groups. Through recognizing the frame pages in the site documents and constructing the frame subframe relation set, the subframe pages that influence the final mining result can be efficiently filtered. Second, we enhance the mining algorithm with the consideration of both the site topology and the content of the web pages. By the introduction of the normalized content link ratio of the web page and the group interlink degree of the page group, the enhanced algorithm concentrates more on the content pages that are less interlinked together. The experiments show that the new approach can effectively reveal more interesting page groups, which would not be found without these enhancements.

Selecting An Appropriate Interestingness Measure to Evaluate the Correlation between Chinese Medicine Syndrome Elements and Symptoms

To select the best interestingness measure appropriate for evaluating the correlation between Chinese medicine （CM） syndrome elements and symptoms, 60 objective interestingness measures were selected from different subjects. Firstly, a hypothesis for a good measure was proposed. Based on the hypothesis, an experiment was designed to evaluate the measures. The experiment was based on the clinical record database of past dynasties including 51 186 clinical cases. The selected data set in this study had 44 600 records. Cold and heat were selected as the experimental CM syndrome elements. Three indicators calculated according to the distances between two CM syndrome elements were obtained in the experiment and combined into one indicator. The Z score, φ-coefficient, and Kappa were selected from 60 measures after the experiment. The Z score and φ-coefficient were selected according to subjective interestingness. Finally, the φ-coefficient was selected as the best measure for its low The method introduced in this paper may be used in other similar territories.

Procreation Anxiety in Climate Crisis:Comparative Analysis of The Smog Society and Diary of an Interesting Year

The deterioration of the environment caused by climate change has been entangled with other factors to wane people’s desire for having children.This paper takes two climate short stories,The Smog Society by the Chinese SF author Chen Qiufan and Diary of an Interesting Year by the British writer Helen Simpson as case studies,comparing the writing of the climate change induced fertility anxiety in the two stories from both the individual and community perspectives.By associating the textual analysis with the social reality about fertility rate in China and Britain,the paper explores performance and coping methods of fertility anxiety in the face of climate crisis,aimed at providing possible solutions for the sustainable development of population.

CARM:Context Based Association Rule Mining for Conventional Data

This paper is aimed to develop an algorithm for extracting association rules,called Context-Based Association Rule Mining algorithm(CARM),which can be regarded as an extension of the Context-Based Positive and Negative Association Rule Mining algorithm(CBPNARM).CBPNARM was developed to extract positive and negative association rules from Spatiotemporal(space-time)data only,while the proposed algorithm can be applied to both spatial and non-spatial data.The proposed algorithm is applied to the energy dataset to classify a country’s energy development by uncovering the enthralling interdependencies between the set of variables to get positive and negative associations.Many association rules related to sustainable energy development are extracted by the proposed algorithm that needs to be pruned by some pruning technique.The context,in this paper serves as a pruning measure to extract pertinent association rules from non-spatial data.Conditional Probability Increment Ratio(CPIR)is also added in the proposed algorithm that was not used in CBPNARM.The inclusion of the context variable and CPIR resulted in fewer rules and improved robustness and ease of use.Also,the extraction of a common negative frequent itemset in CARM is different from that of CBPNARM.The rules created by the proposed algorithm are more meaningful,significant,relevant and insightful.The accuracy of the proposed algorithm is compared with the Apriori,PNARM and CBPNARM algorithms.The results demonstrated enhanced accuracy,relevance and timeliness.

An Effective Network Traffic Data Control Using Improved Apriori Rule Mining

The increasing usage of internet requires a significant system for effective communication. To pro- vide an effective communication for the internet users, based on nature of their queries, shortest routing path is usually preferred for data forwarding. But when more number of data chooses the same path, in that case, bottleneck occurs in the traffic this leads to data loss or provides irrelevant data to the users. In this paper, a Rule Based System using Improved Apriori (RBS-IA) rule mining framework is proposed for effective monitoring of traffic occurrence over the network and control the network traffic. RBS-IA framework integrates both the traffic control and decision making system to enhance the usage of internet trendier. At first, the network traffic data are ana- lyzed and the incoming and outgoing data information is processed using apriori rule mining algorithm. After generating the set of rules, the network traffic condition is analyzed. Based on the traffic conditions, the decision rule framework is introduced which derives and assigns the set of suitable rules to the appropriate states of the network. The decision rule framework improves the effectiveness of network traffic control by updating the traffic condition states for identifying the relevant route path for packet data transmission. Experimental evaluation is conducted by extrac- ting the Dodgers loop sensor data set from UCI repository to detect the effectiveness of theproposed Rule Based System using Improved Apriori (RBS-IA) rule mining framework. Performance evaluation shows that the proposed RBS-IA rule mining framework provides significant improvement in managing the network traffic control scheme. RBS-IA rule mining framework is evaluated over the factors such as accuracy of the decision being obtained, interestingness measure and execution time.

An Improved Algorithm for Mining Correlation Item Pairs

Apriori algorithm is often used in traditional association rules mining,searching for the mode of higher frequency.Then the correlation rules are obtained by detected the correlation of the item sets,but this tends to ignore low-support high-correlation of association rules.In view of the above problems,some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm.It can dig item sets with low-support but high-correlation.Although the algorithm has pruned the search space,it is not obvious that the performance of the running time based on the big data set is reduced,and the correlation pairs can be meaningless.This paper presents an improved mining algorithm with new association rules based on interestingness for correlation pairs,using an upper bound on interestingness of the supersets to prune the search space.It greatly reduces the running time,and filters the meaningless correlation pairs according to the constraints of the redundancy.Compared with the algorithm based on the Phi correlation coefficient,the new algorithm has been significantly improved in reducing the running time,the result has pruned the redundant correlation pairs.So it improves the mining efficiency and accuracy.

Extracting Leading Joint Causes of Death and Mining Associations between Them

The gains in analyzing death from a multiple cause perspective have been recognized for a very long time. Methods that have been adopted have sought to determine additional gains made by treating death as a multiple cause phenomenon as compared to analysis based on a single under-lying cause. This paper shows how association rules mining methodology can be adapted to determine joint morbid causes with strong and interesting associations. Results show that some causes of death that do not appear among the leading causes show strong associations with other causes that would otherwise remain unknown without the use of association rules methodology. Overall, the study found that the leading joint pair of causes of death in South Africa was metabolic disorders and intestinal infectious diseases which accounted for 18.9 deaths per 1000 in 2008, followed by cerebrovascular and hypertensive diseases which accounted for 18.3 deaths per 1000.

并非“有趣”的interesting

提到interesting，许多学生都认为它是用来形容令人感兴趣的事物。如我们可将自己爱读的书、爱听的故事、爱看的电影描述为an interesting book，an interesting story，an interesting film等等。总之，只要我们认为是有趣的东西，似乎都可以用interesting来形容。

IT在高职英语教学中的应用

在英语教学中,培养和激发学生的学习兴趣是非常重要的,尤其是高职英语教学,教师要通过有趣的教学活动,全面调动学生的思维和感官,激发学生学习兴趣,提高教学效果。

RING3表达沉默细胞系的构建及其对Cyclin A的诱生

应用RNA干扰技术,建立了RING3(reallyinteresting gene3)表达沉默的细胞系,研究了RING3内生水平的表达与其可能的靶基因Cyclin A之间的关系.结果表明,在血清饥饿的成纤维细胞NI H/3T3中,用血清刺激后会引起细胞周期蛋白Cyclin A的表达;当用RNAi技术使RING3表达抑制后,Cyclin A的表达受到相应影响,可见Cyclin A的表达受到RING3的调节,其转录激活受到RING3和E2F-1等因子的共同调控,表明RING3与肿瘤发生之间的关系可能与Cyclin A的表达有关.

Some Important Elements In Language Teaching

Nowadays, the connection between people becomes closer and closer. English as one of the most popular used language in the world is universally learned. English teaching thus becomes significant. Also English teachers play a significant role in modern society. A good teacher should rack his brain to make his lessons interesting so as to stimulate students' motivation. A teacher should choose a kind of teaching approach ,which is suitable for his students and texts and he should also show his enthusiasm to the students at class. So his students can be affected by him.

General Psychiatry Highlights

In issues 2 and 3, some interesting and popular topics are presented and they may inspire new ideas in psychiatric research. A systematic review conducted by Dr Chen and her colleagues has drawn much attention to the worldwide media, that it was positive to treat anxiety symptoms by regulating intestinal flora (RIF).

Biodiverse rotifer assemblage (Rotifera： Eurotatoria) of floodplain lakes of the Brahmaputra basin of lower Assam, northeast India： composition and ecosystem diversity

The study aims to ascertain the hypothesis on the rich rotifer biodiversity of the floodplain lakes(beels) of the Brahmaputra river basin and to use these metazoans to assess trophic status or to characterize habitat variations of wetlands. The plankton samples collected from four beels of lower Assam revealed 160 Rotifera species belonging to 35 genera and 19 families. The richness is of biodiversity value as ~38.0% and ~57.0% of the rotifer species known till date from India and northeast India(NEI), respectively. One species each is new to the Oriental region and NEI, and three species are new to Assam; 23 species merit global biogeography interest and several exhibit distribution values in the Indian sub-region. The diverse Lecanidae > Brachionidae > Lepadellidae > Trichocercidae and speciose littoral-periphytic L ecane > Lepadella > Trichocerca, and richness of Brachionus spp. following removal of aquatic macrophytes are noteworthy. Overall rotifer composition showed homogeneity amongst beels while lower monthly richness and community similarities affirmed heterogeneity within individual beels. We propose L/B quotient based on L ecane : Brachionus species ratios to characterize habitat variations of the sampled wetlands. Sláde?ek's B/T quotient based on B rachionus : T richocerca species ratios affirmed general 'meso-trophic' status of diff erent beels. Our results provided little insight on the influence of individual abiotic factors but the canonical correspondence analyses asserted higher cumulative influence of ten abiotic parameters on Rotifera richness in each beel.

Neural Regeneration Research(NRR) Emphasis and Direction for 2009

In 2009, NRR will emphasis on novel findings in the mechanism research of nerve cells and tissue regeneration, involved in structure change, interactions and specific properties of nerve cells and tissue elements during development and disease. The journal has focused on research concerning the histomorphological changes of nerve cells,

Neural Regeneration Research

Nenral Regeneration Research （NRR） is a first-class international academic journal indexed in SCI. It is supervised by the Ministry of Health, sponsored by the Chinese Assoeiation of Rehabilitation Medicine, and published by Science Press and the Editorial Board of NRR.

Neuroscience Events in June

Neural Regeneration Research (NRR) is an international academic journal specialized in the field of neural regeneration research and published in English. The journal is supervised by

Neural Regeneration Research--An interesting SCI-indexed journal in neuroregeneration

Neural Regeneration Research （NRR） is an international academic journal specialized in the field of neural regeneration research and published in English. The journal is supervised by the Ministry of Health, P.R. China, sponsored by the Chinese Association of Rehabilitation Medicine, and co-edited by the Editorial Department of Neural Regeneration Research and China Science Press.

Neural Regeneration Research

Neural Regeneration Research （NRR） is a first-class international academic journal indexed in SCI. It is supervised by the Ministry of Health, sponsored by the Chinese Association of Rehabilitation Medicine, and published by Science Press and the Editorial Board of NRR.

eural Regeneration Research-- An interesting SCI-indexed journal in neuroregeneration

Neural Regeneration Research （NRR） is an international academic journal specialized in the field of neural regeneration research and published in English. The journal is supervised by the Ministry of Health, P.R. China, sponsored by the Chinese Association of Rehabilitation Medicine, and co-edited by the Editorial Department of Neural Regeneration Research and China Science Press.

Electrical Resistivity Survey in Bukit Bunuh, Malaysia for Subsurface Structure of Meteorite Impact Study

An electrical resistivity tomography (ERT) study was conducted at Bukit Bunuh, Lenggong Perak (Malaysia). The study is to justify the features and environmental subsurface geological structure which is due to the meteorite impact. The ERT survey used resistivity equipments comprises of 4 survey lines with 5 m electrode intervals, covering an area of approximately 64 km2. The survey lines were carried out using ‘roll-along’ technique. The data were processed and analysed using RES2DINV, Excel and Surfer software in order to produce electrical resistivity tomography for qualitative interpretations. The results show the variation of resistivity value and faults. The 2-D resistivity results generally show the study area was divided into two main zones, alluvium with resistivity value of 10 - 800 Ωm, and bedrock with resistivity value of > 1500 Ωm and depth of 20 - 40 m. There are lots of fractured zones which are different than normal, identified along the survey lines. The South-North line shows the fractured zones were identified at 760 - 3800 m and 4700 - 5900 m. The West-East line, the fractured zone was identified at 1545 - 6570 m and North-West to South-East line, the fractured zone was identified at 740 - 5850 m. Meanwhile, South-West to North-East line, the fractured zone was identified at 720 - 1520 m. These interesting results were indicated at position of longitude;100.965 - 100.978 and latitude;5.056 - 5.066 where the bedrock depth is 40 - 60 m MSL and highly fractured. The area was surrounded by high elevated bedrock. Integration of 2-D resistivity results with boreholes is successful give valid and reliable results. The results of the study indicate that these geophysical approaches have a capability of retrieving the meteorite impact subsurface of the studied area.