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Many long non-coding RNAs (lncRNAs) have been found to play crucial roles in sepsis-induced acute kidney injury (AKI), including lncRNA nuclear-enriched abundant transcript 1 (NEAT1). We aimed to further elucidate the functions and molecular mechanism of NEAT1 in sepsis-induced AKI. Sepsis-induced AKI cell model was established by treatment with lipopolysaccharide (LPS) in human tubule epithelial (HK2) cells. Cell viability and apoptosis were determined by Cell Counting Kit-8 (CCK-8) assay and flow cytometry, respectively. Western blot assay was performed to measure all protein levels. The concentrations of inflammatory factors were evaluated using enzyme-linked immunosorbent assay (ELISA). The expression levels of inflammatory factors, NEAT1, microRNA-93-5p (miR-93-5p), and thioredoxin-interacting protein (TXNIP) were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The oxidative stress factors were detected using corresponding kits. The interaction between miR-93-5p and NEAT1 or TXNIP was predicted by bioinformatics analysis and verified by dual-luciferase reporter and RNA Immunoprecipitation (RIP) assays. NEAT1 was upregulated in serum of sepsis patients and LPS-induced HK2 cells. NEAT1 silence alleviated LPS-induced HK2 cell injury by inhibiting apoptosis, inflammation and oxidative stress. Moreover, miR-93-5p was a direct target of NEAT1, and suppression of NEAT1 weakened LPS-induced injury by upregulating miR-93-5p in HK2 cells. Furthermore, TXNIP was a downstream target of miR-93-5p, and miR-93-5p attenuated LPS-induced HK2 cell injury by downregulating TXNIP. In addition, NEAT1 regulated TXNIP expression by acting as a sponge of miR-93-5p. NEAT1 might aggravate LPS-induced injury in HK2 cells by regulating miR-93-5p/TXNIP axis, providing a potential therapeutic strategy for sepsis-associated AKI.

Bergenia scopulosa (Saxifragaceae) is an endangered perennial herb which is endemic to China. In the present study, the complete chloroplast genome of B. scopulosa was determined by using Illumina pair-end sequencing. The complete chloroplast genome of B. scopulosa was 156,041 bp, consisting of a pair of inverted repeat (IR) regions (25,585 bp each), a small single copy (SSC) region (18,354 bp) and a large single copy (LSC) region (86,517 bp). The chloroplast genome of B. scopulosa contained 132 genes, including 85 protein-coding genes, 37 tRNA genes and eight ribosomal RNA genes. The overall GC content of the whole genome is 37.8%. Phylogenetic analysis of 23 selected chloroplast genomes revealed that B. scopulosa was closely related to Heuchera parviflora var. saurensis.

First-generation epithelial growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have markedly improved the treatment of non-small cell lung cancer (non-SCLC) with EGFR-sensitive mutations. However, acquired resistance to these drugs was inevitable. The transformation of lung adenocarcinoma to SCLC following treatment with EGFR-TKIs is a rare phenomenon that contributes to resistance to EGFR-TKIs. The present case concerns a 74-year-old man previously diagnosed with and treated for pneumonia; however, this was later pathologically confirmed as lung adenocarcinoma by transbronchial lung biopsy. Deletion of exon 19 of EGFR was identified by next-generation sequencing technology. The patient improved markedly when treated with gefitinib, but relapsed after 1 year, with markedly increased serum levels of neuron-specific enolase (NSE). Transformation to SCLC was detected by endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) re-biopsy, which was negative for the deletion of exon 19 of EGFR. The patient was positive for vimentin expression and refractory to etoposide and cisplatin chemotherapy, and succumbed to the disease 18 months after diagnosis. Transformation of the disease from adenocarcinoma to SCLC may have been due to cancer heterogeneity. Re-biopsy is therefore important in EGFR-TKI-resistant patients for genetic and histological re-evaluation. NSE serum levels may also be useful for detecting early SCLC transformation.

Two cationic silicone surfactants, 3-[tri-(trimethylsiloxy)]silylpropylpyridinium chloride (Si 4 pyrCl) and N -methyl-3-[tri-(trimethylsiloxy)]silylpropylpiperidinium chloride (Si 4 pipCl), were synthesized. Their aggregation behavior in aqueous solution was investigated through analyses of surface tension, electrical conductivity, dynamic light scattering (DLS), and transmission electron microscopy (TEM). Surface-tension measurements showed that the two cationic silicone surfactants decreased the surface tension of water to almost 20 mN m − 1 . This result indicated the surfactants' remarkable surface activity. The effects of inorganic salts, sodium chloride, sodium bromide, sodium iodide and sodium sulfate, on the aggregation behavior of Si 4 pyrCl and Si 4 pipCl were systematically explored. Results showed that the aggregation of Si 4 pyrCl and Si 4 pipCl was promoted by the addition of salts and that aggregation ability followed the order of NaI > NaBr > Na 2 SO 4 > NaCl. Thermodynamic parameters obtained from electrical-conductivity measurements indicated that the micellization of Si 4 pyrCl and Si 4 pipCl was entropy driven. Spherical aggregates with diameters ranging from 200 nm to 600 nm were observed by TEM, and the aggregates' diameter distribution was obtained by DLS. The extraction behavior on several metal ions (Co (II), Mn (II), Fe (III), Ni (II), Cu (II), Al (III), Sn (IV), Zn (II), Ce (III), Li (I), Mg (II), Au (III), and Pd (II)) in chloroform by the surfactants in chloroform was studied for the first time. Results showed that Si 4 pipCl and Si 4 pyrCl had good extraction ability for Au (III) and Pd (II).

In this study, we synthesized the cationic silicone surfactant tri-(trimethylsiloxy)silylpropylpyridinnium chloride (Si 4 pyrCl). We then systematically investigated the effects of organic salts such as sodium acetate, sodium oxalate, sodium citrate, sodium benzoate, and sodium salicylate on the aggregation behavior of Si 4 pyrCl in aqueous solution through surface tension and electrical conductivity analyses, dynamic light scattering (DLS), and transmission electron microscopy (TEM). The addition of organic salts promoted surfactant aggregation. The aggregation ability was observed to be in the following order: s sodium salicylate > sodium benzoate > sodium citrate > sodium oxalate > sodium acetate. The measurement of electrical conductivity shows that the micellization of Si 4 pyrCl in aqueous solution is spontaneous. Several spherical-like aggregates with a diameter of approximately 500 nm were observed via TEM. The diameter distribution was determined through DLS. This work will be of great significance for the understanding of cationic silicone surfactants and their applications in industrial production.

The silicone ionic liquid, 1-methyl-3-[tri-(trimethylsiloxy)]silylpropyl-imidazolium chloride ([Si 4 mim]Cl), was first used for the construction of the W/O microemulsion system and the [Si 4 mim]Cl/ n -heptane/ n -hexanol/NaCl microemulsion system was applied for palladium extraction for the first time. The stability of [Si 4 mim]Cl/ n -heptane/ n -hexanol/NaCl microemulsion system was characterized by the Turbiscan Lab. For the Pd (II) extraction by the [Si 4 mim]Cl/ n -heptane/ n -hexanol/NaCl microemulsion system, primary parameters (namely, the vibration time, the [Si 4 mim]Cl concentration, the phase ratio and the additives) affecting the palladium extraction was investigated to optimize the process. Under the optimum conditions, the extraction percentage of Pd (II) is up to 98%. Afterwards, the ionic-exchange mechanism of Pd (II) extraction by the [Si 4 mim]Cl/ n -heptane/ n -hexanol/NaCl microemulsion system was confirmed by the Job Method and analyzed by FT-IR spectra. The stripping of Pd (II) from the microemulsion phase was also studied using the NaCl solutions, indicating a high stripping efficiency. At last, the selectivity of the [Si 4 mim]Cl/ n -heptane/ n -hexanol/NaCl microemulsion system to Pd (II) from other metals (Cu (II), Co (II), Ni (II), Fe (III), Al (III) Zn (II), Ce (III), Li (I), Mg (II) and Sn (IV)) was demonstrated to be quite high. The results of our work indicate that the [Si 4 mim]Cl/ n -heptane/ n -hexanol/NaCl microemulsion system is a promising approach for Pd (II) extraction.

Backgrounds Pulmonary sarcoidosis is often complicated by pulmonary hypertension, a complication that is associated with increased disability and mortality. To this point, however, little progress has been made in the treatment of sarcoidosis associated with pulmonary hypertension (SAPH). Methods A prospective study was performed on 72 consecutive Chinese sarcoidosis patients followed at an outpatient clinic. The patients were evaluated by Doppler echocardiography and computed tomography pulmonary angiography. SAPH was confirmed by right heart catheterisation. The clinical parameters were compared before and 2 months after treatment with oral glucocorticoids. Eight stage III and IV patients with moderate to severe proximal pulmonary arterial stenosis (PAS) and SAPH underwent interventional therapy (IT) after prednisone treatment and were followed up at 3-month intervals. Results After 2 months of prednisone treatment, 32 stage III and IV patients continued to display varying degrees of PAS and SAPH. Eight patients underwent IT without severe complications and made improvements in pulmonary arterial pressure, pulmonary vascular resistance, arterial oxygen saturation and WHO functional classification, with the improvements lasting more than 3 months. Conclusions PAS caused by external compression in sarcoidosis is a significant reason for SAPH. IT is effective and safe in the treatment of PAS and SAPH.

Background The incidence and risk factors of chronic thromboembolic pulmonary hypertension (CTEPH) in patients with acute pulmonary embolism (PE) have been well reported. However, in real world, patients diagnosed with PE for the first time were usually composed of acute PE, sub-acute PE, and chronic PE, and the cumulative incidence and risk factors of CTEPH in this cohort were still unknown. Methods A prospective, long-term, follow-up study was conducted to assess the incidence of symptomatic CTEPH in consecutive patients with PE diagnosed for the first time. Patients with unexplained persistent dyspnea during follow-up underwent transthoracic echocardiography and, if the findings indicated pulmonary hypertension, ventilation-perfusion lung scanning and right heart catheterization. CTEPH was confirmed if perfusion defects were present, mean pulmonary artery pressure (mPAP) ≥25 mmHg and pulmonary artery wedge pressure (PAWP) ≤15 mmHg. Results The cumulative incidence of CTEPH in patients with PE diagnosed for the first time was 11.2% at 3 months, 12.7% at 1 year, 13.4% at 2 years, and 14.5% at 3 years. The following factors increased the risk of CTEPH: time from symptoms to treatment of PE ≥1 month (odds ratio (OR), 14.77), intermediate (OR, 37.63) to high risk PE (OR, 39.81), segmental and sub-segmental branch location of embolism (OR, 8.30) and PE-related primary risk factors (OR, 5.01). 9.4% of CTEPH patients developed from acute PE, and 90.6% from sub-acute and chronic PE. Conclusions In real world, CTEPH is a relatively common and serious complication in PE patients diagnosed for the first time. Early diagnosis and treatment of PE will decrease the incidence of CTEPH in these unspecified patients.

Background In clinical practice, longitudinal data can be used to find trend patterns of pathema progress, such as tumour progress, along a time axis. This kind of data can be treated as time-series data. The maximum common sub-sequence is the most common method for calculating similarity of time-series data; and each point is normally treated as having the same weight. However, not all points of data within the time series should be given the same importance. According to clinical experience, the later period sub-sequence (closer to death) has a more significant effect than earlier periods in a trend analysis. Results A weighted-similarity measure based on LCSS with Constraint Window (W-LCSS-CW) Method is proposed. The results obtained from the time-series data using different weighting factors are discussed. In a study of non-small cell lung cancer using time-series data, the relative evaluation method and external evaluation method were adopted to calculate cluster effect. The results show that the proposed method, W-LCSS-CW, can improve clustering performance significantly. Clustering performance of various methods was performed using a comparison of (Cindex/Mindex). The proposed W-LCSS-CW Method was evaluated to 1.55 which was 37.02%, 48.01%, 49.64% higher than other common methods (Euclidean, DTW, STS) respectively. Conclusions The proposed W-LCSS-CW Method is recommended for monitoring time-series data of tumour patients because the incorporated weighting factor provides more convincing cluster results for medical assist support.

In this study' a model selection procedure for varying-coefficient model based on longitudinal data is proposed to distinguish three types of variables: variables not in the model' variables in the model with time-independent coefficients and variables in the model with time-varying coefficients. To identify these three kinds of variables simultaneously' we extend the present variable selection method from cross-sectional data to longitudinal data. This method combines the B-spline function approximation and Adaptive-Lasso penalty to perform variable selection and do nonparametric estimation simultaneously. Validity is illustrated with a set of simulation experiments' and results indicate the proposed variable selection procedure performs well in distinguishing the real type of independent variables.

BACKGROUND: Monotherapy and sequential combination therapy have been widely used in the treatment of pulmonary arterial hypertension (PAH). There is limited evidence for initial combination therapy in patients with PAH, particularly those with World Health Organization (WHO) functional class III or IV. METHODS: Twenty-seven consecutive treatment-naive PAH subjects with WHO functional class III or IV PAH were randomized into 3 groups with a 1:1:1 ratio: a combination therapy group with 125 mg of bosentan twice daily plus 10 μg of iloprost 4–6 times/d; a bosentan monotherapy group with 125 mg of bosentan twice daily; and a iloprost monotherapy group with 10 μg of iloprost 4–6 times/d. Clinical and hemodynamic data were collected at baseline, 6 weeks, and 3 months. The primary end point was the change in the 6-min walk distance (6MWD) from baseline values. RESULTS: At baseline, there were no differences in demographics, WHO classification, hemodynamics, classification of PAH, or 6MWD among the 3 groups. The 6MWD significantly improved in the combination therapy group compared with the bosentan monotherapy and iloprost monotherapy groups at week 6 (P = .001) and after 3 months (P CONCLUSIONS: Initial combination therapy in treatment-naive PAH subjects with WHO functional class III or IV can significantly improve 6MWD, hemodynamics, and quality of life compared with monotherapy. Further studies with large samples and placebo controls are required to assess the tolerability and efficacy of initial combination therapy in patients with PAH. (ClinicalTrials.gov registration NCT01712997).

Effect of three inorganic electrolytes (LiCl, NaCl, and MgCl2) and four organic electrolytes, viz. tetraalkylammonium bromides ((CH3)4NBr, (C2H5)4NBr, (C3H7)4NBr, and (C4H9)4NBr) on the aggregation behavior of the anionic halogen-free surface active ionic liquid, 1-butyl-3-methylimidazolium dodecylsulfate ([C4mim][C12SO4]), in aqueous solution was studied by surface tension, steady-state fluorescence quenching, and dynamic light scattering measurements. The results show that all the electrolytes investigated have a salting-out effect, which promotes aggregate formation of [C4mim][C12SO4]. The stronger hydrophobicity of organic electrolytes is crucial for the superior influence on the surface activity of [C4mim][C12SO4]. However, the stabilization energy results obtained by quantum chemical calculations prove that although the promoting effect of organic cations (tetraalkylammonium cations) on the micellization process of [C4mim][C12SO4] is powerful, they mainly act as counterions. For a given electrolyte (i.e., NaCl), critical micelle concentration of [C4mim][C12SO4] decreases with increasing electrolyte concentration. The average aggregation number and aggregate size of [C4mim][C12SO4] were shown to change slightly in the presence of various electrolytes, except for MgCl2. Anyway, hydrophobicity together with bulkiness and hydration ability of cations of the added electrolytes are suggested to play important roles in modifying the aggregation behavior of [C4mim][C12SO4] in aqueous solution.

The traditional k-means algorithm is often calculated according to the Euclidean distance. For longitudinal data it is unable to perform accurate and efficient computing. Based on extended Frobenius-norm (Efros) distance, in this study we proposed a method to improve the selection of initial centers for k-means clustering. This method can improve the traditional k-means clustering on longitudinal data. For missing longitudinal data, we first adopted a linear interpolation strategy to fill in missing values and then standardized the data, etc. Through comprehensive simulation studies, we demonstrate the power and effectiveness of our method by comparing the similarity within and between the classes. The results of our experiments show that our method can cluster the longitudinal data more effectively.

Pulmonary sarcoidosis is often complicated by pulmonary hypertension, a complication that is associated with increased disability and mortality. To this point, however, little progress has been made in the treatment of sarcoidosis associated with pulmonary hypertension (SAPH).A prospective study was performed on 72 consecutive Chinese sarcoidosis patients followed at an outpatient clinic. The patients were evaluated by Doppler echocardiography and computed tomography pulmonary angiography. SAPH was confirmed by right heart catheterisation. The clinical parameters were compared before and 2 months after treatment with oral glucocorticoids. Eight stage III and IV patients with moderate to severe proximal pulmonary arterial stenosis (PAS) and SAPH underwent interventional therapy (IT) after prednisone treatment and were followed up at 3-month intervals.After 2 months of prednisone treatment, 32 stage III and IV patients continued to display varying degrees of PAS and SAPH. Eight patients underwent IT without severe complications and made improvements in pulmonary arterial pressure, pulmonary vascular resistance, arterial oxygen saturation and WHO functional classification, with the improvements lasting more than 3 months.PAS caused by external compression in sarcoidosis is a significant reason for SAPH. IT is effective and safe in the treatment of PAS and SAPH.

Chinese text classification is always challenging, especially when data are high dimensional and sparse. In this paper, we are interested in the way of text representation and dimension reduction in Chinese text classification. First, we introduces a topic model — Latent Dirichlet Allocation(LDA), which is uses LDA model as a dimension reduction method. Second, we choose Support Vector Machine(SVM) as the classification algorithm. Next, a method of text classification based on LDA and SVM is described. Finally, we choose documents with large number of Chinese text for experiment. Compared with LDA method and the traditional TF∗IDF method, the experimental results show that LDA method runs a better results both on the classification accuracy and running time.

The web reviews contain a lot of features of the evaluation object and express the viewpoints or attitudes of the reviewers. Therefore, analyzing them and identifying the sentiment polarity will be significantly important and valuable. This paper uses the appearing-frequency of noun words to extract the aspect words and uses some semantic rules to extract opinion words to form the aspect -- opinion word pairs. We use the sentiment orientation-point mutual information (SO-PMI) algorithm to calculate the sentiment strength of opinion words and get the semantic orientation of the opinion words and improved the algorithm. With the Chinese reviews of doctors from the medical websites www.39.net and www.chan120.net, experimental results demonstrate the validity of the proposed method.

In the study of gestational hypertension, most of studies focused on whether a risk factor is associated with gestational hypertension. However, according to the clinical experience, it is important to know the effects of risk factors on women's blood pressure during pregnancy. Thus, we examined the effects of known risk factors (age, hematocrit, etc.) over gestational age. We also examined whether the effects of known risk factors are different between gestational hypertension group and preeclampsia group. These were studied in 412 pregnant women including 1874 clinical follow-up records. On the longitudinal clinical data of pregnant women, varying coefficient models were applied to study the effects of known risk factors over gestational age. The results showed that the effects of known risk factors varied with gestational age, and the changing processes of known risk factors over gestational age were different between gestational hypertension group and preeclampsia group. In final, we used the relative error as the criterion to assess the accuracy of the estimated varying coefficient model. The relative errors for total clinical data, gestational hypertension group and preeclampsia group were 13.3%, 8.1% and 14.3%, respectively.

Ontology, as a knowledge representation approach, continues to evolve over time as the domain develops. It is of particular importance when introducing ontologies into the information integration field, to eliminate semantic conflicts brought about by changes along the time axis. This paper first introduces a temporal ontology model which can be used to express and deal with time related information, then defines a set of rich query operators and a basic reasoning operator. Further, a prototype Temporal Ontology Management System (TOMS) enhanced with the above operators is applied to an information integration background with temporal semantic conflicts. Testing shows that TOMS is both capable of managing temporal ontologies and supporting temporal queries and basic reasoning.

With the purpose of extracting potential knowledge from the vast amounts of data, as well as providing auxiliary information for decision making for college admissions departments, in this paper, based on SPSS 12.0 software clementine, it mainly uses C5.0 decision tree algorithm and association rules Apriori algorithm to study the college entrance examination enrollment data, students' performance in college and employment data. It mainly focuses on the data preparation process, and shows the mining process aimed at two different goals and the valuable information dug out during these processes. The results of study shows that this kind of information can provide decision making for the department in charge of admissions. Keywords-data mining; admissions; clementine; decision

Many people use the web as the main information source in their daily lives. However, most web pages contain non-information components, such as site bars, footers and ads, etc., which make it complicated to extract text from the original HTML documents. Because of the high human intervention and the low results extraction quality, although the web text extraction techniques have been developed, the popularization and efficiency of the usage still need to be solved.. In this paper, we proposed a maximum subsequence segmentation (MSS) algorithm and discussed its application in the domain of news web sites. Differing from the tree structure analysis and VIPS, the algorithm divided the web into text segmentation and label segmentation. Experiment shows that the MSS algorithm achieves 93.73% accuracy over 2000 news pages from 5 different news sites and the efficiency is much faster than DOM-based using same dataset.

User interests drift modeling is the fundamental and key technology of Personal Recommendation System (PRS), and is arising more and more attention by researcher from home and abroad. At present, web user interests drift model is in its original phase for the reason of many aspects, and there also exist some problems need to be studied continually and deeply. Considering of web user interests might change with time flying, huge of surfing data and many influence factors need to be concerned, because user interests changes constantly with time flying. A novel web user interest drift pattern modeling method is proposed. First, this paper takes user interests as time series via using hidden Markvo model, which may properly map the sequential characteristics of user interests. Second, improved GSP searching algorithm is used to find the frequent pattern from user interest sequence. Finally, forgetting mechanism is used to solve interests drift problem, and time window is used to store current user interest pattern, and the old interests will elapse with the new interests coming constantly. Plenty of online experiments were done to verify the reasonability of the user interests drift model. Via experiments, conclusion can be drawn that this method can work perfectly and efficiently, which may firmly grasp user interests drift rule in time. Therefore, personal recommendation system using these interests drift model can recommend the latest information for web user, only according to user's potential interests changing.

Background- In the study of rules in pathological changes, most of the traditional analyses are from the static perspective, which regard cross-sectional data as the input dataset to analyze the effect of non-time-varying factors. However, according to the clinical experiences, the changes of physical status can partly reflect the disease progression and the mortality which have been ignored in the existing studies. Thus, based on the dynamic perspective, by using the changing patterns of symptom as the model input, longitudinal data can be utilized to further explore the rules in pathological changes from the dynamic perspective which is a novel and effective solution. Method- The study proposed a dynamic pattern representation method; pretreated and transformed the original dataset, including the Traditional Chinese Medicine TCM and the western medicine clinical longitudinal data, into a 2-dimensional matrix composed of the symptom indexes and the changing patterns; and analyzed the influences between the changing patterns of symptom and III stage non-small cell lung cancer NSCLC patient's mortality by multivariate logistic regression. Result- The predicting accuracy using the transformed dataset by proposed representation method is 90.7%. Based on the enter stepwise regression method, the accuracy increased 26.3% and 14.5% than the baseline dataset and the last records respectively; based on the forward stepwise regression method, the accuracy increased 16.7% and 3% than the baseline dataset and the last records respectively. Conclusion- The experiment results indicated that the proposed data representation method is feasible and effective, meanwhile, the proposed novel dynamic perspective appears more appropriate for the TCM mainly III stage NSCLC patients' modeling than the traditional static method.

To ensure the sustainable development of the Internet community, satisfy the demand for the network user's access, this paper introduces how to use the K-means algorithm to divide the network community user group and improve the FP-tree algorithm (CDFP-tree) to analyse the characteristics of the network user group. The purpose is to explore the relationship between the user group's interest, purpose and the natural attribute. The result will be the technical support for the personalized network services. Another focus of this paper is placed on optimizing and improving the FP-tree algorithm which is based on the constraint item, mainly through the adjustment of the method of construction tree and traverse of the trees to realize. The experiments show that comparing to the original algorithm, the CDFP-tree has the same accuracy while the efficiency is highly improved. And the results of the characteristic analysis have a referenced value to the personalized recommendation service.

Aiming at the irregular and uneven feature of medical time series data, a novel algorithm based on piecewise slope transformation distance for short time series similarity measure is propose. We firstly do some preprocess based on algorithm for key points selected, make the data curve to zigzag shape, then, we measure the distance between two curves based on piecewise slope transformation algorithm. By experiments, conclusion can be draw that this new approach can measure distance rapidly and correctly, especially appropriate to short time series data.

In data mining processing, filling incomplete data is very important in preprocessing of data mining project. An algorithm based on time series similarity measurement for incomplete data is proposed, this approach can fill missing data via following internal rule of data set reasonably. By experiments, we can draw a conclusion that algorithm is effective on condition that incomplete data are no more than half of the whole data in one case.

The performance of dimensionality reduction on multiple, relevant, and uncertain data is not satisfied by a single method. Therefore, in this paper, we proposed a two-stage reduction method based on rough set and factor analysis (RSFA). This method integrates the advantages of feature selection on treating relevant and the advantages of rough set (RS) reduction on maintaining classification power. At first, a RS reduction is used to remove superfluous and interferential attributes. Next, a factor analysis is utilized to extract common factors to replace multi-dimension attributes. Finally, the RSFA is verified by using traditional Chinese medical clinical data to predict patients’ syndrome. The result shows that less attributes and more accuracy can be expected with RSFA, which is an appropriate reduction method for such problems.

An inverted index structure of path that based on domain ontology is proposed in this paper. The all of distinct entities in domain ontology are indexed; and for each distinct entity an inverted list, storing the entity and the identifiers of the path containing the entity, and experimental results show that the index structure is more suitable for the query of multiple keywords and it can eliminate the ambiguity and achieve the semantic expansion of query keywords.

A Max-Probability Density based Clustering (MPDC) algorithm is proposed in this paper to resolve the problem of Word Sense Disambiguation in semantic document. MPDC take the context information of a keyword based on WordNet into account and select the max probability sense by measuring the density of the concept. We also do experiment on semantic documents retrieving from Swoogle and Watson, two famous semantic web searching engines. The result shows MPDC get a good efficiency.

Semantic similarity between concepts is a fundamental problem and plays an important role in many applications of artificial intelligence, knowledge sharing and Web mining. In this paper, a new measure based on semantic ontology database WordNet is proposed which combines information content-based measure and the edge-counting techniques to measure semantic similarity. "PART-OF" and "IS-A" hierarchical relations’ influence are considered on the semantic similarity in this paper. Breadth-first search is used to find the shortest path between two concepts. The similarity of hiberarchy and superposition are calculated respectively. WordNet3.0 is employed; JWNL1.4.1 is used to operate WordNet. According to the experiment against a benchmark set by human similarity judgment, our measure achieves a better result.

To meet the needs of personal semantic query in information integrated systems, this paper applied role preference ontologies to express the preferences information belonged to different roles. Especially, we focused on self-maintenance of the role preference ontologies. It analyzed the query history of the registered user and calculated the preference weight value of the role preference ontology by using the formula of TF×IDF. The role preference ontology composed of a series of conceptions, sub-conceptions, attributions, instances and their preference weight values. Consequently, the system could return the personal semantic query results according to the preference information of the role preference ontologies.

Ontologies are significant for the development of the semantic web, which could implement the information reusing and knowledge sharing. With the number of ontologies increasing rapidly, ontology mapping is a useful method to clear up the heterogeneity among ontologies so that ontologies could understand each other properly. Structures information is important for mining semantic relation during ontology mapping. In the ontology hierarchy, vertical information is the main factor used in many mapping methods, while the horizontal relation is not employed fully yet. In this paper, from the aspect of the dimensions of the concept in ontologies, which describes the horizontal relation of ontology concepts, an ontology mapping approach is proposed. The values on concept dimensions could be named concepts, intersections, unions, complements or restrictions. They are compared with ontology concepts to help ontology mapping. Experiments indicate that the concept dimension is an important factor infecting ontology mapping.

There are a lot benefits to enable intelligent agent understanding the information from semantic web. It enhances the efficiency of information usage and at the same time, suffices the need of users. Semantic documents contain adequate semantic information which helps understanding. However, discrepancy between ontology which is an interpreter of semantic document prevents the share of knowledge. In this paper, we proposed a uniform representation for the content, which include concepts and relations, of semantic documents based on WordNet. First, disambiguation is preceded within the key words in a document for the purpose of mapping them to concepts. Then we present the whole document in the form of concept graph that Levenshtein Distance could be applied for making a classification of documents. We have empirical result that this methodology makes a promising raise in accuracy.

To meet requirements of personal query, a personal query framework including personal ontology and role ontology is proposed based on preference ontology. The two-tier structure of the preference semantic formalization shows the differences and commonness of the background knowledge among different users. It is possible to generate personal ontology and role ontology automatically and to maintain them by the historical query records and analysis modules in the framework. Comparing with current methods, this framework is able to implement personal semantic query and make it possible to create and maintain the two-tier ontology structure highly automatically because of the personal semantic preference formal expression.

In view of inevitable redundancies in local data sources in heterogeneous information integration systems, a multi-copy join optimization method (MuCoJo for short) based on a genetic algorithm is proposed. MuCoJo can choose appropriate redundant copies of the tables to participate a joint query and optimizes the join order of it. By using the redundant copies, MuCoJo enlarges the search space so that the concurrent executions of different local sources can be best used. Meanwhile, MuCoJo could take advantage of redundancies features in such systems and get faster joint query response time. Experimental results show the computational efficiency of the MuCoJo and its necessity in information integration system. Moreover, during the population initialization, controlling invalid solutions can reduce the search space effectively at the cost of initialization time consuming.