INTERNATIONAL CONFERENCE ON WEB RESEARCH | Year:2017 | دوره:3 |Papers Count:31

IN RECENT YEARS, WE ARE FACED WITH LARGE AMOUNTS OF SPORADIC UNSTRUCTURED DATA ON THE WEB. WITH THE EXPLOSIVE GROWTH OF SUCH DATA, THERE IS A GROWING NEED FOR EFFECTIVE METHODS SUCH AS CLUSTERING TO ANALYZE AND EXTRACT INFORMATION. BIOLOGICAL DATA FORMS AN IMPORTANT PART OF UNSTRUCTURED DATA ON THE WEB. PROTEIN SEQUENCE DATABASES ARE CONSIDERED AS A PRIMARY SOURCE OF BIOLOGICAL DATA. CLUSTERING CAN HELP TO ORGANIZE SEQUENCES INTO HOMOLOGOUS AND FUNCTIONALLY SIMILAR GROUPS AND CAN IMPROVE THE SPEED OF DATA PROCESSING AND ANALYSIS. PROTEINS ARE RESPONSIBLE FOR MOST OF THE ACTIVITIES IN CELLS. THE MAJORITY OF PROTEINS SHOW THEIR FUNCTION THROUGH INTERACTION WITH OTHER PROTEINS. HENCE, PREDICTION OF PROTEIN INTERACTIONS IS AN IMPORTANT RESEARCH AREA IN THE BIOMEDICAL SCIENCES. MOTIFS ARE FRAGMENTS FREQUENTLY OCCURRED IN PROTEIN SEQUENCES. A WELL-KNOWN METHOD TO SPECIFY THE PROTEIN INTERACTION IS BASED ON MOTIF CLUSTERING. EXISTING WORKS ON MOTIF CLUSTERING METHODS SHARE THE PROBLEM OF LIMITATION IN THE NUMBER OF CLUSTERS. HOWEVER, REGARDING THE VAST AMOUNT OF MOTIFS AND THE NECESSITY OF A LARGE NUMBER OF CLUSTERS, IT SEEMS THAT AN EFFICIENT, SCALABLE AND FAST METHOD IS NECESSARY TO CLUSTER SUCH LARGE NUMBER OF SEQUENCES. IN THIS PAPER, WE PROPOSE A NOVEL APPROACH TO CLUSTER A LARGE NUMBER OF MOTIFS. OUR APPROACH INCLUDES EXTRACTING MOTIFS WITHIN PROTEIN SEQUENCES, FEATURE SELECTION, PREPROCESSING, DIMENSION REDUCTION AND UTILIZING BIGFCM (A LARGE-SCALE FUZZY CLUSTERING) ON SEVERAL DISTRIBUTED NODES WITH HADOOP FRAMEWORK TO TAKE THE ADVANTAGE OF MAPREDUCE PROGRAMMING. EXPERIMENTAL RESULTS SHOW VERY GOOD PERFORMANCE OF OUR APPROACH.

WEB SERVICE COMBINATION IS AN IMPORTANT TASK PERFORMED IN DIFFERENT PHASES OF THE SERVICE-ORIENTED ARCHITECTURE LIFECYCLE. MEASURING SERVICE QUALITY BASED ON THE NON-FUNCTIONAL CHARACTERISTICS IS AN EXCEEDINGLY DIFFICULT TASK. THEREFORE, THIS PAPER PRESENTS A MULTILAYER PERCEPTRON ARTIFICIAL NEURAL NETWORK (MLPANN) TO PROVIDE A METHOD FOR MEASURING QUALITY OF SERVICE IN A SERVICE-ORIENTED ARCHITECTURE AND TO IMPROVE NETWORK PERFORMANCE. PARTICLE SWARM OPTIMIZATION (PSO) IS USED TO OPTIMIZE THE WEIGHTS OF THE NETWORK. FINALLY, OUR RESULTS ARE COMPARED TO THOSE OF A COMBINATION OF DIFFERENT EVOLUTION (DE) ALGORITHM AND MLPANN IN TERMS OF MEAN SQUARE ERROR (MSE), ROOT MEAN SQUARE ERROR (RMSE) AND STANDARD DEVIATION (STD). THE RESULTS DEMONSTRATE THE SUPERIORITY OF THE PROPOSED METHOD.

IN OUR MODERN WORLD, SEARCH ENGINES HAVE BEEN PROPOSED AS ONE OF THE CHALLENGING RESEARCH AREAS. ONE OF THE MAIN ISSUES IN SEARCH ENGINES STUDIES IS HUMAN COMPUTER INTERACTION, WHICH ITS AIM IS TO UNDERSTAND USER’S NEEDS. IF THERE IS NO RIGHT QUERY PROCESSING APPROACH, THE RESULTS WILL BE INVALID IN MOST CASES. THEREFORE, IN THIS PAPER WE PRESENT A NEW APPROACH TO PROCESS AND ANALYZE THE QUERIES FOR SPATIAL SEARCH ENGINES. OUR ALGORITHM IS IMPLEMENTED IN THE THREE STEPS, INCLUDING: ITERATIVE SEGMENTATION OF THE QUERY, SUB-QUERIES PROCESSING BY FINDING APPROPRIATE CANDIDATES FOR THE LOCATION-NAMES, THE LOCATION-TYPES AND SPATIAL RELATIONSHIPS AND FINALLY CHECKING THE RELATIONSHIPS AMONG THESE CANDIDATES IN VALIDATION PHASE. GENERALLY USING OUR METHOD HAS TWO MAJOR ADVANTAGES AS THE SEARCH ENGINES CAN PROVIDE THE CAPABILITY OF SPATIAL ANALYSIS BASED ON THE SPECIFIC PROCESS WHICH LEADS TO A BETTER INTERACTION BETWEEN THE USERS AND THE SEARCH APPLICATION IN GEOSPATIAL REALM AND SECONDLY BECAUSE OF THE DISAMBIGUATION TECHNIQUE, USER REACHES THE MORE DESIRABLE RESULT.

CURRENTLY, STANDARD ENCRYPTION ALGORITHMS, SUCH AS AES, ARE USED FOR ENCRYPTION OF DATA IN CLOUD. AS AES ALGORITHM IS A LOW-SPEED FOR SERIAL, IN ADDITION TO SOLVING ITS LOW-SPEED, A PARALLEL ALGORITHMS IS INTRODUCED. REGARDING THE EXTENT OF CLOUD NETWORK, THE MOST IMPORTANT FEATURE OF THE PROPOSED ALGORITHM IS ITS HIGH SPEED AND RESISTIVITY AGAINST THE ATTACKS. THE ALGORITHM IS DESIGNED AND IMPLEMENTED IN JAVA SCRIPT IN CLOUDSIM ENVIRONMENT. THE RESULTS OBTAINED FROM IMPLEMENTATION OF THIS ALGORITHM IN CLOUD SIMULATING ENVIRONMENT, ARE COMPARED AND EVALUATED RELATIVE TO THE OTHER ALGORITHMS. SIMILAR INPUT WAS FED TO THE PROPOSED AND OTHER ALGORITHMS. THE PROPOSED ALGORITHM PROCESSED THE DATA IN 82 MS WHICH IS FASTER THAN THE OTHER ALGORITHM.

RDF MODELS ARE WIDELY USED IN THE WEB OF DATA DUE TO THEIR FLEXIBILITY AND SIMILARITY TO GRAPH PATTERNS. BECAUSE OF GROWING USE OF RDFS, THEIR VOLUMES AND CONTENTS ARE INCREASING. THEREFORE, PROCESSING OF SUCH AMOUNT OF DATA ON A SINGLE MACHINE IS NOT EFFICIENT ENOUGH, BECAUSE OF THE RESPONSE TIME AND LIMITED HARDWARE RESOURCES. AS A RESULT, TO PROCESS THIS DATA MODEL, CLUSTER PROCESSING IS INTRODUCED. ONE OF THESE CLUSTER PROCESSING TOOLS IS APACHE HADOOP. BECAUSE OF USING TOO MUCH OF HARD DISKS, THE RESPONSE TIME IS USUALLY UNACCEPTABLE. IN THIS PAPER, ACCORDING TO THIS PROBLEM, WE USE APACHE SPARK FOR RAPID PROCESSING OF RDF DATA MODELS. ONE KEY FEATURE OF APACHE SPARK IS USING MAIN MEMORY INSTEAD OF HARD DISK, SO THE SPEED OF DATA PROCESSING IS IMPROVED. IN CONTINUES, WE WILL RUN SQL QUERY ON RDF DATA WHICH PARTITIONED ON THE CLUSTER.

THE EMERGENCE OF ELECTRONIC COMMERCE LED TO A SITUATION THAT MANY COMPANIES TEND TO TAKE ADVANTAGE OF THIS SPACE, BUT THE MAIN PROBLEM WITH THIS TYPE OF BUSINESS IS TO RETAIN CUSTOMERS AND BUILD LOYALTY IN THEM. EASE OF ACCESS TO OTHER COMPANIES IN CASE OF DISSATISFACTION ALLOWS CUSTOMERS TO QUICKLY REFER TO OTHER COMPETING COMPANIES. THEREFORE, CUSTOMER SATISFACTION IS VERY IMPORTANT.CONSIDERING THE IMPORTANCE OF CUSTOMER LOYALTY IN THIS BUSINESS, IN THIS STUDY THE IMPACTS OF SOME AFFECTING FACTORS IN ELECTRONIC LOYALTY WAS INVESTIGATED. THIS STUDY IS USING THE SAMPLES OF 378 PEOPLE OBTAINED FROM COCHRAN FORMULA THAT HAVE BEEN SELECTED FROM ONE OF THE NEIGHBORHOODS OF TEHRAN CALLED NARMAK WITH A POPULATION OF 25, 000 PEOPLE AND THEY ALL HAD THE EXPERIENCE OF ONLINE SHOPPING. IN THIS STUDY, SPSS SOFTWARE AND MULTIVARIATE REGRESSION ANALYSIS WERE USED FOR DATA ANALYSIS.THE RESULT OF THIS STUDY SHOWED THAT THE QUALITY OF SERVICES, WEBSITE QUALITY, INFRASTRUCTURE AND ELECTRONIC SHOPPING EXPERIENCE IN THE ORDER OF PRIORITY HAS AN IMPACT ON ELECTRONIC LOYALTY. IT IS WORTH MENTIONING THAT CONSIDERING THE SURVEY RESULTS OF THIS RESEARCH THEY CAN BE USED FOR OBTAINING CUSTOMER SATISFACTION IN E-COMMERCE.

SINCE THE USE OF INTERNET HAS INCREDIBLY INCREASED, IT BECOMES AN IMPORTANT SOURCE OF KNOWLEDGE ABOUT ANYTHING FOR EVERYONE. THEREFORE, THE ROLE OF SEARCH ENGINE AS AN EFFECTIVE APPROACH TO FIND INFORMATION IS CRITICAL FOR INTERNET'S USERS. THE STUDY OF SEARCH ENGINE USERS' BEHAVIOR HAS ATTRACTED CONSIDERABLE RESEARCH ATTENTION. THESE STUDIES ARE HELPFUL IN DEVELOPING MORE EFFECTIVE SEARCH ENGINE AND ARE USEFUL IN THREE POINTS OF VIEW: FOR USERS AT THE PERSONAL LEVEL, FOR SEARCH ENGINE VENDORS AT THE BUSINESS LEVEL, AND FOR GOVERNMENT AND MARKETING AT SOCIAL SOCIETY LEVEL. THESE KINDS OF STUDIES CAN BE DONE THROUGH ANALYZING THE LOG FILE OF SEARCH ENGINE WHEREIN THE INTERACTIONS BETWEEN SEARCH ENGINE AND THE USERS ARE CAPTURED. IN THIS PAPER, WE AIM TO PRESENT ANALYSES ON THE QUERY LOG OF A WELL-KNOWN AND MOST USED PERSIAN SEARCH ENGINE. OUR ANALYSES ARE PRESENTED IN THREE MAIN CATEGORIES: 1) STATS-BASED ANALYSES, 2) TEMPORAL-BASED ANALYSES, AND 3) TOPIC-BASED ANALYSES. THE OBTAINED RESULTS ARE PROMISING. MOBILE USERS OFTEN POSTED QUERIES IN WEEKENDS, WHEREAS WEB USERS UTILIZE THE SEARCH ENGINE IN WORKWEEKS. THE MAJORITY OF QUERIES POSTED FORM MOST-POPULATED CITIES. ADDITIONALLY, IRANIANS ARE MOSTLY INTERESTED IN POLITICAL, SOCIAL, AND ECONOMICAL TOPICS.

SOCIAL MEDIA PLACE WHERE PEOPLE COMMUNICATE AND SHARE THEIR IDEAS PROVIDE RICH INFORMATION FOR SOCIAL NETWORK ANALYSIS. THERE ARE VARIOUS ANALYSES SUCH AS INFORMATION DIFFUSION MODELING AND COMMUNITY DETECTION WHICH ARE USED TO ANALYZE DATA OF SOCIAL NETWORKS.IN THIS PAPER, WE INVESTIGATE SOME NOVEL ASPECTS OF HASHTAG DIFFUSION AMONG IRANIAN COMMUNITIES IN INSTAGRAM IN THE PERIOD OF THE LAST LEGISLATIVE ELECTION IN IRAN. AFTER DATA PREPARATION, WE ANALYZE THE VALIDATION OF THREE DIFFERENT ASSUMPTIONS. FIRST, WE STUDY THE EFFECTS OF FOLLOWER-FOLLOWEE RELATIONS IN THE SPREAD OF THE CAMPAIGN HASHTAGS. BASED ON THE TIMESTAMPS OF THE POSTS, WE INVOKE NETRATE METHOD TO ESTIMATE INFORMATION DIFFUSION RATES OVER EDGES OF FOLLOWER-FOLLOWEE NETWORK. THEN, BY APPLICATION OF LOUVAIN METHOD AS A COMMUNITY DETECTION ALGORITHM, WE INVESTIGATE THE RELATION OF COMMUNITY MEMBERSHIP AND CONTAGION TRANSMISSION RATE. FINALLY, WE STUDY OBSERVED TOPICAL PREFERENCES IN NETWORK COMMUNITIES.RESULTS SHOW THE FLOW OF INFORMATION FROM FOLLOWEES TO FOLLOWERS WITH A SIGNIFICANT RATE OF DIFFUSION OVER THE WHOLE NETWORK. HOWEVER, BEING PART OF A SPECIFIC COMMUNITY DOES NOT CONTRIBUTE TO BE EXPOSED TO A CASCADE FASTER THAN OTHERS. WHILE THE COMMUNITIES WERE DEFINED BASED ON MODULARITY MAXIMIZATION AND NO INFORMATION RELATED TO HASHTAGS INVOLVED, A TOPICAL PREFERENCE ALSO IS OBSERVED WITHIN THE COMMUNITIES’ HASHTAGS WHICH HAD THE SAME ORIENTATION AS OBSERVED IN TWO MAJOR POLITICAL PARTIES OF IRAN.

WITH THE RAPID GROWTH OF THE INTERNET AND THE SPREAD OF THE INFORMATION CONTAINED THEREIN, THE VOLUME OF INFORMATION AVAILABLE ON THE WEB IS MORE THAN THE ABILITY OF USERS TO MANAGE, CAPTURE AND KEEP THE INFORMATION UP TO DATE. ONE SOLUTION TO THIS PROBLEM ARE PERSONALIZATION AND RECOMMENDER SYSTEMS. RECOMMENDER SYSTEMS USE THE COMMENTS OF THE GROUP OF USERS SO THAT, TO HELP PEOPLE IN THAT GROUP MORE EFFECTIVELY TO IDENTIFY THEIR FAVORITE ITEMS FROM A HUGE SET OF CHOICES.IN RECENT YEARS, THE WEB HAS SEEN VERY STRONG GROWTH IN THE USE OF BLOGS. CONSIDERING THE HIGH VOLUME OF INFORMATION IN BLOGS, BLOGGERS ARE IN TROUBLE TO FIND THE DESIRED INFORMATION AND FIND BLOGS WITH SIMILAR THOUGHTS AND DESIRES. THEREFORE, CONSIDERING THE MASS OF INFORMATION FOR THE BLOGS, A BLOG RECOMMENDER SYSTEM SEEMS TO BE NECESSARY.IN THIS PAPER, BY COMBINING DIFFERENT METHODS OF CLUSTERING AND COLLABORATIVE FILTERING, PERSONALIZED RECOMMENDER SYSTEM FOR PERSIAN BLOGS IS SUGGESTED.

WITH THE PROLIFERATION OF THE INTERNET AND INCREASED GLOBAL ACCESS TO ONLINE MEDIA, CYBERCRIME IS ALSO OCCURRING AT AN INCREASING RATE. CURRENTLY, BOTH PERSONAL USERS AND COMPANIES ARE VULNERABLE TO CYBERCRIME. A NUMBER OF TOOLS INCLUDING FIREWALLS AND INTRUSION DETECTION SYSTEMS (IDS) CAN BE USED AS DEFENSE MECHANISMS. A FIREWALL ACTS AS A CHECKPOINT WHICH ALLOWS PACKETS TO PASS THROUGH ACCORDING TO PREDETERMINED CONDITIONS. IN EXTREME CASES, IT MAY EVEN DISCONNECT ALL NETWORK TRAFFIC. AN IDS, ON THE OTHER HAND, AUTOMATES THE MONITORING PROCESS IN COMPUTER NETWORKS. THE STREAMING NATURE OF DATA IN COMPUTER NETWORKS POSES A SIGNIFICANT CHALLENGE IN BUILDING IDS. IN THIS PAPER, A METHOD IS PROPOSED TO OVERCOME THIS PROBLEM BY PERFORMING ONLINE CLASSIFICATION ON DATASETS. IN DOING SO, AN INCREMENTAL NAIVE BAYESIAN CLASSIFIER IS EMPLOYED. FURTHERMORE, ACTIVE LEARNING ENABLES SOLVING THE PROBLEM USING A SMALL SET OF LABELED DATA POINTS WHICH ARE OFTEN VERY EXPENSIVE TO ACQUIRE. THE PROPOSED METHOD INCLUDES TWO GROUPS OF ACTIONS I.E. OFFLINE AND ONLINE. THE FORMER INVOLVES DATA PREPROCESSING WHILE THE LATTER INTRODUCES THE NADAL ONLINE METHOD. THE PROPOSED METHOD IS COMPARED TO THE INCREMENTAL NAIVE BAYESIAN CLASSIFIER USING THE NSL-KDD STANDARD DATASET. THERE ARE THREE ADVANTAGES WITH THE PROPOSED METHOD: (1) OVERCOMING THE STREAMING DATA CHALLENGE; (2) REDUCING THE HIGH COST ASSOCIATED WITH INSTANCE LABELING; AND (3) IMPROVED ACCURACY AND KAPPA COMPARED TO THE INCREMENTAL NAIVE BAYESIAN APPROACH. THUS, THE METHOD IS WELL-SUITED TO IDS APPLICATIONS.

CLOUD COMPUTING EMPLOYS PARALLEL AND DISTRIBUTED COMPUTING CONCEPTS TO PROVIDE USERS WITH SHARED RESOURCES THROUGH THE INTERNET. ONE OF THE MOST IMPORTANT ISSUES WHICH ARE RAISED IN A CLOUD ENVIRONMENT IS TASK SCHEDULING ON EXISTING RESOURCES; SO THAT ON THE ONE HAND IT CAN PROVIDE USER’S REQUIREMENTS, SUCH AS MINIMUM RUN TIME OR COST AND ON THE OTHER HAND WITH THE PROPER USE OF RESOURCES, CAN ALSO CAUSE SERVICE PROVIDERS’ BENEFITS.IN THIS PAPER WE EXTENDED A RECENT HEURISTIC ALGORITHM CALLED BLACK HOLE OPTIMIZATION (BHO) AND PRESENT A MULTI OBJECTIVE SCHEDULING METHOD FOR WORKFLOW APPLICATION BASED ON PARETO OPTIMIZER ALGORITHM. OUR PROPOSED METHOD CAN CONSIDER USER REQUIREMENTS AND ALSO THE INTERESTS OF SERVICE PROVIDERS. USING THE BALANCED AND UNBALANCED WORKFLOW WE COMPARED OUR PROPOSED METHOD WITH ALGORITHMS OF SPEA2 AND NSGA2 BASED ON THE PARAMETERS OF COMPLETION TIME AND COST AND RESOURCE EFFICIENCY.

THE RAPID GROWTH OF CLOUD SERVICES AND THE GROWING USER DEMANDS GAIN RESOURCES ARE THE REASON OF THE DEVELOPMENT AND POPULARITY OF THE CLOUD NETWORKS. THIS ENVIRONMENT GIVES USERS THE ILLUSION OF INFINITE RESOURCES SO THEY CAN BE USED RESOURCES ON DEMAND. CLOUD RESOURCE PROVIDERS WANT TO GAIN MORE EFFICIENCY FROM ITS OWN RESOURCES. THEIR MAIN AIM IS TO REDUCE COST AND MAXIMIZE REVENUE FROM PROVIDING SERVICES TO USERS. USERS ALSO WANT TO MINIMIZE HER/HIS COSTS AND ACHIEVE TO ADEQUATE EFFICIENCY. THE PROPER USE OF RESOURCES IN THE CLOUD IS A CHALLENGE. PROPER SCHEDULING OF TASKS IS AN IMPORTANT ISSUE AND RESPOND TO THE REQUEST IN THE SHORTEST TIME REQUIRES A CORRECT MANAGEMENT OF RESOURCES, WHICH CAN HANDLE MANY REQUESTS WITH THE NUMBER OF SOURCES IDENTIFIED.REDUCE THE TIME, IS ONE OF THE MAIN CONCERNS OF CLOUD RESOURCE PROVIDERS, ON THE OTHER HAND, USER RELIABILITY IS VERY IMPORTANT. TIME AND RELIABILITY ARE TWO CONFLICTED AIMS, IMPROVING THESE AIMS TOGETHER IS THE MAIN PURPOSE OF THIS STUDY. THIS RESEARCH APPLIED MULTI-OBJECTIVE OPTIMIZATION METHOD WHICH CONSIDER SEVERAL CONFLICTING OBJECTIVES TOGETHER.

THIS STUDY PRESENTS A MODEL OFFERING PEOPLE WHICH FOOD IS HEALTHIER AND MAKES THEM MORE SATISFIED BASED ON THEIR MOODS AND FOOD CONSUMPTION BEHAVIORS. THE SOCIAL NETWORK ANALYSIS TECHNIQUES ARE APPLIED ON THE FOOD CONSUMPTION OF THE PEOPLE WHOM WERE RECORDED IN INFORMATION SYSTEMS. THE IMPLEMENTATION METHOD IS ACCORDING TO THIS PROCEDURE: FIRST, PEOPLE CLASSIFIED TO 6 GROUPS BASED ON THEIR NUTRITION STYLE GETTING FROM THE ISLAMIC TRADITIONAL MEDICINE AND SOME PREVIOUS PAPERS IN THE MODERN MEDICINE. THEN, A DATA NETWORK WAS MADE FROM PEOPLE’S RELATIONSHIPS. AFTERWARDS, A MODEL HAS BEEN PRESENTED BASED ON THE ANALYSIS OF THAT NETWORK. TO EVALUATE THIS MODEL, THE PROPOSED METHOD IS APPLIED ON A UNIVERSITY’S SELF-SERVICE RESTAURANT SYSTEM. THE RESULTS SHOW THAT PEOPLE WITH A HEALTHY OR "HOT AND WET" TEMPERAMENT NUTRITION STYLE, HAVE PERSONALITY TRAITS OF "EXTRAVERSION", "OPENNESS" AND "CONSCIENTIOUSNESS". MOREOVER, PEOPLE WITH A TRADITIONAL NUTRITION STYLE OR "COLD AND WET" TEMPERAMENT NUTRITION, ARE PEOPLE WITH PERSONALITY TRAITS OF "INTROVERSION" AND "NEUROTICISM".

TODAY PEOPLE USE THE INTERNET TO FIND THE ANSWER TO THEIR QUESTIONS. THEY MOSTLY RATHER ASK OTHER USERS ON COMMUNITY QUESTION ANSWERING (CQA) SITES FOR AN ANSWER THAN JUST SEARCHING THE WEB. HOWEVER, AS SOCIAL MEDIA BECOMES MORE POPULAR, USERS TEND TO ASK THEIR QUESTIONS ON THESE NETWORKS, AND IGNORE THE BENEFITS CQA SITES OFFER. ON THE OTHER HAND, AUTOMATIC QUESTION ANSWERING (QA) SYSTEMS ARE UNABLE TO COMPREHEND QUESTIONS INCLUDING IMAGES AND IMPLEMENTING NECESSARY ALGORITHMS FOR SUCH SYSTEMS IS EXPENSIVE. IN THIS PAPER, WE PROPOSE QA PROCESS BASED ON CROWDSOURCING, WHICH RUNS ON A QA OPEN SYSTEM. THE SYSTEM BENEFITS FROM CROWDSOURCING ADVANTAGES, BESIDES AUTOMATION TECHNIQUES. THE MODEL IS OPERATIONAL AND WE HAVE DEMONSTRATED THAT QUESTIONS COULD BE RECEIVED FROM DIFFERENT HETEROGENEOUS SOURCES, IF THE SUITABLE PROCEDURES ARE USED, AND THAT THE ANSWER IS OBTAINED FROM THE CROWD IN THE PROPOSED PROCESS BASED ON CROWDSOURCING. MOREOVER, THE FIRST IRANIAN CROWDSOURCING PLATFORM FOR COMPLICATED TASKS IS IMPLEMENTED, WHICH COULD BE USED AS A BASIS FOR FUTURE RESEARCH.

THE GROWTH OF SEMANTIC WEB TECHNOLOGIES UNDERPINS THE EVER-INCREASING DEVELOPMENT OF LINKED DATA AND THEIR APPLICATIONS. IN RECENT YEARS, THE NUMBER OF LINKED DATA SOURCES HAS BEEN RAISED FROM 12 TO MORE THAN 2973 SETS. THE DATASETS ARE MANAGED AS DECENTRALIZED SOURCES, AND THEIR QUALITY IS A SERIOUS CONCERN. THE ASSESSMENT OF THE QUALITY OF LINKED DATA IS A KEY TO ADOPTING THEM IN DIFFERENT FIELDS BECAUSE EACH DATA SET HAS BEEN DEVELOPED BY A DIFFERENT GROUP, USING VARIOUS METHODS AND TOOLS. MOREOVER, CROWDSOURCING CONTRIBUTES AS ONE OF THE MAIN STRATEGIES IN DATA COLLECTION. THIS CONTRIBUTION IS SEEN IN THE TOURISM INDUSTRY OR E-COMMERCE FIELDS AND DESERVES ATTENTION. THE QUALITATIVE AND QUANTITATIVE DIVERSITY OF SUCH DATA IS HIGHER THAN THOSE GENERATED BY OFFICIAL ORGANIZATIONS AND FIRMS. IN THIS PAPER, WE FIRST OVERVIEW AND EVALUATE THE DIMENSIONS AND MEASURES FOR THE QUALITY ASSESSMENT OF DATA. THEN, WE PRESENT A NOVEL FRAMEWORK AS A SOLUTION FOR IMPROVING LINKED DATA QUALITY EVALUATION AND DATA FUSION. FINALLY, WE ADOPT SEVERAL TOOLS TO ASSESS THE QUALITY OF DATA OF SOME REPUTABLE DATA SOURCES USING THE PROPOSED FRAMEWORK.

THE STUDY OF SOCIAL STRUCTURE AND THE EFFECT OF IT ON SOCIAL MEMBERS IS AN ATTRACTIVE AREA IN SOCIAL NETWORKS. STRUCTURAL BALANCE THEORY FOCUSES ON PATTERNS OF SIGNED LINKS AND FREQUENCY/POPULARITY OF THEM. IN RECENT YEARS SEVERAL WORKS TRY TO DEFINE SOME APPROXIMATIONS TO CALCULATE THE DISTANCE OF ONE UNBALANCED GRAPH FROM NEAREST BALANCED ONE. BUT THESE WORKS DON’T HAVE ANY IDEA ABOUT THE LINKS WITH UNSTABLE SIGNS THAT CHANGING THEIR SIGN MAKES THE NETWORK MORE BALANCED. ALSO, SOME WORKS INTRODUCE A CENTRALIZED ALGORITHM TO DETECT THESE LINKS. IN THIS PAPER, WE HAVE INTRODUCED A LOCALIZED ALGORITHM FOR DETECTING AND CHANGING THE SIGN OF THESE LINKS AS A SOURCE OF TENSION. THE RESULTS OF SIMULATION FOR SEVERAL SCALE-FREE NETWORKS WITH DIFFERENT FEATURES SHOW THAT PROPOSED ALGORITHM HAS THE ABILITY TO MOVE THE NETWORK TO A BALANCED ONE. AS THE PROPOSED ALGORITHM FOCUSES ON COMPONENTS OF THE SOCIAL NETWORK TO CALCULATE LOCALIZED MEASURES, IT IS APPROPRIATE FOR AGENT-BASED MODELS TO STUDY OTHER SOCIAL PHENOMENA.

IN THIS PAPER WE INVESTIGATE A PERSIAN SEARCH ENGINE LOG AND PRESENT A COMPREHENSIVE ANALYSIS OF QUESTION QUERIES IN THREE LEVELS: STRUCTURE, CLICK AND TOPIC. BY ANALYZING QUESTION QUERIES CHARACTERISTICS, WE EXPLORE BEHAVIOR OF PERSIAN LANGUAGE USERS. OUR EXPERIMENTAL RESULTS SHOW THAT QUESTION QUERIES LENGTH ARE LARGER THAN NORMAL QUERIES. MOST OF THESE QUERIES CONTAINED QUESTION WORDS "HOW" AND "WHAT" AND THEIR TOPICS WERE MAINLY ABOUT HEALTH, POLICY, RELIGION AND SOCIETY.

VULNERABILITIES IN WEB APPLICATIONS ARE DUE TO VARIOUS FACTORS. FAILURE TO PROPERLY VALIDATE USER INPUT IS ONE OF THE FACTORS THAT LED TO RUN UNAUTHORIZED CODE IN THESE PROGRAMS. SQLI AND XSS ARE TWO COMMON VULNERABILITIES IN WEB APPLICATIONS, THAT DUE TO LACK OF PROPER INPUT VALIDATION. THEREFORE, IN THIS PAPER WE STUDY HOW TO PROTECT ORGANIZATIONAL WEBSITES OF NORTH KHORASAN IN IRAN AGAINST SQLI AND XSS VULNERABILITIES. WE HAVE ANALYZED ELEVEN WEBSITES. TEN OF WEBSITES RELATED TO GOVERNMENT ORGANIZATION AND ONE OF THEM IS PRIVATE ORGANIZATION. THESE WEB SITES HAVE BEEN TESTED WITH TAKE LICENSES FROM THE RELEVANT ORGANIZATION.

THIS WORK ADDRESSES THE PROBLEM OF ENABLING MACHINES TO PERFORM SCIENTIFIC TASKS, E.G. REASONING BASED ON SCIENTIFIC LAWS AND DEFINITIONS, RECOGNIZING INTER-DEPENDENCE OF SCIENTIFIC DOMAINS, AND ANSWERING QUERIES ABOUT SCIENCE CORPUS. THE BUILDING BLOCKS OF SCIENCE, SUCH AS SCIENTIFIC TERMS, LAWS, PROBLEMS, SOLUTIONS, THEORIES AND DISCIPLINES ARE TRADITIONALLY REPRESENTED AS SINGLE, ATOMIC NODES IN SCIENTIFIC ONTOLOGIES. THIS MAKES IT DIFFICULT TO DISTINGUISH THOSE CONSTITUENTS AND USE THEM PROPERLY IN THE AUTOMATION OF SCIENTIFIC ACTIVITIES.WE SUPPORT THE IDEA OF ADDING STRUCTURE TO THE REPRESENTATION OF DIFFERENT CONSTITUENTS OF SCIENCE CORPUS. THE STRUCTURE OF A SCIENTIFIC LAW, FOR INSTANCE, WOULD BE DIFFERENT FROM THAT OF A SOLUTION TO A GIVEN SCIENTIFIC PROBLEM. IT IS SHOWN THROUGH EXAMPLES THAT CONSIDERING THOSE DIFFERENT STRUCTURES CAN HELP IN REASONING ABOUT SCIENTIFIC KNOWLEDGE. MOREOVER, THE DOMAIN-INDEPENDENT ASPECTS OF DIFFERENT CONSTITUENTS OF SCIENCE HAVE THE POTENTIAL TO BE FACTORED OUT IN A META-ONTOLOGY. THISMETA-SCIENCE CAN ALSO CONTAIN GENERAL REASONING MACHINERY ABOUT SCIENCE.

THE DISCOVERY AND ANALYSIS OF COMMUNITY STRUCTURES IN NETWORKS IS VERY HELPFUL IN MANY FIELDS. DESPITE EXISTING WELL-KNOWN QUALITY METRICS FOR DETECTING AND EVALUATING COMMUNITIES, EACH OF THEM HAS ITS OWN LIMITATIONS. IN THIS PAPER WE WILL DISCUSS DEEPLY THESE LIMITATIONS FOR COMMUNITY DETECTION AND EVALUATION BASED ON THE DEFINITIONS AND FORMULATIONS OF THESE QUALITY METRICS.

USER BEHAVIOR MODELING IS ONE OF WEB USAGE MINING APPLICATIONS HELPING TO UNDERSTAND THE BEHAVIOR OF A USER WHILE INTERACTING WITH THE WEB. SINCE THE ACTIVITY INFORMATION OF USERS ARE RECORDED IN WEB LOG FILES, LOG DATA IS THE STARTING POINT FOR ANY WEB MINING PROCESS. THUS, THE QUALITY OF RESULTS STRONGLY DEPENDS ON THE QUALITY OF INPUT DATA. IN THIS PAPER, THE RESULT OF OUR SCENARIO-BASED EXPERIMENT IN PREPROCESSING LOG DATA FOR ANALYZING USER BEHAVIOR IS PRESENTED. THE PROPOSED METHOD IS PRACTICALLY APPLIED ON FERDOWSI UNIVERSITY OF MASHHAD (FUM) LOG DATA AND THE RESULTS ARE DISCUSSED.

BROWSER-BASED GAMES ARE PLAYED DIRECTLY IN WEB BROWSERS, AND NATURALLY, THEY DO NOT NEED ANY ADDITIONAL SOFTWARE OR PLUG-IN INSTALLATIONS. THIS FEATURE IS ONE OF THE PRIMARY ADVANTAGES OF ONLINE AND BROWSER-BASED GAMES TO THE OFFLINE GAMES WHICH ONE COULD INSTALL ON HIS/HER TARGET PLATFORM. THERE ARE COUNTLESS CHALLENGES THAT CAUSE LOTS OF GAME PROGRAMMERS TO AVOID ONLINE GAMES SUCH AS, THE VARIETY OF WEB BROWSERS AND THEIR DIVERSITY IN THE INTERNET SPEED AND BANDWIDTH, AND YET THE GAME MUST BE USABLE FOR EVERY USER WITH ANY BROWSER USING DIFFERENT BANDWIDTH. THERE ARE VAST GAME ENGINES THAT CAN DESIGN ONLINE GAMES; BUT THE ONLY DRAWBACK IS DUE TO THEIR COMPLICATED STRUCTURES, YIELDS THE RESULTS NOT ALWAYS BE THAT LIGHT TO CAPABLE ON LOADING SIMPLY ON VARIOUS COMPUTERS. THUS, IN THIS PAPER, WE DESIGNED A FOOTBALL GAME USING THE BASIC TECHNOLOGIES OF GAME ENGINES SUCH AS WEBGL, HTML5, AND THREE.JS TO AVOID COMPLEX STRUCTURES AND ACHIEVE ADVANCED SPEED AND CONVENIENCE FOR DIFFERENT USERS WITH DIFFERENT EQUIPMENT. ALSO, WE DEMONSTRATE THE STRUCTURES AND METHODS OF COLLISION DETECTION IN THE WAY OF OUR DEVELOPMENT. IN THE END, THE RESULTING GAME IS SO LIGHT YET ABSORBING THAT CAN BE RUN ON ANY WEB BROWSERS WITH THE MOST BASIC FEATURES.

TODAY, MOBILE CLOUD COMPUTING HAS BEEN WIDELY USED AND CAN SEND COMPLEX COMPUTATIONS TO THE STRONGER SERVER WITH MORE RESOURCES AND GET RESULTS FROM THEM TO OVERCOME THE LIMITATIONS OF EXISTING MOBILE DEVICES, SUCH AS BATTERY LEVEL, THE AMOUNT OF CPU AND MEMORY. LOCAL MOBILE CLOUDS, WHICH CONSIST OF THE MOBILE DEVICES, ARE USED AS A SUITABLE SOLUTION TO SUPPORT REAL-TIME APPLICATIONS, ESPECIALLY?. DUE TO SHARE BANDWIDTH AND COMPUTING RESOURCES ACROSS ALL MOBILE DEVICES, A TASK SCHEDULING IS REQUIRED TO ENSURE THAT MULTIPLE MOBILE DEVICES CAN EFFECTIVELY ASSIGN WORKS TO LOCAL MOBILE CLOUDS IN SUCH WAY THAT THE TIME LIMITATION IS CONSIDERED AND THE AMOUNT OF REMAINING ENERGY IS ESTIMATED FOR REDUCING ENERGY CONSUMPTION.. IN THIS PAPER, WE SUGGEST ENERGY-AWARE AND ADAPTIVE TASK SCHEDULER. THE TASK SCHEDULER DISCOVERS RESOURCES BASED ON CONTROLLING MESSAGES PERIODICALLY. THIS METHOD, WITH AN ESTIMATION OF TASK COMPLETION TIME, CALCULATES ENERGY CONSUMPTION AND THE AMOUNT OF REMAINING ENERGY IN EACH PROCESSING NODE. THEN, IT SCHEDULES CURRENT WORK WITH A POSSIBLE ADAPTIVE METHOD AT THE PROCESSING NODE AND SETS TIME LIMITATION IN ORDER TO IMPROVE NETWORK EFFICIENCY UNDER UNPREDICTABLE CONDITIONS. THE RESULTS OF TESTS CARRIED OUT ON THE PROPOSED METHOD COMPARED TO EXISTING METHODS SHOW THAT THE PROPOSED METHOD HAS THE LOWEST ENERGY CONSUMPTION PER SUCCESSFUL TASK. MOREOVER, THE PROPOSED METHOD HAS SCALABILITY AND HIGH FLEXIBILITY AND CAN BE DEPLOYED ON ANY NETWORK.

NOWADAYS, SEARCH ENGINES ARE PROMINENT TOOLS, WHICH ARE REQUIRED BY USERS, FOR FINDING INFORMATION IN WEB. MULTIMEDIA SEARCH ENGINES ARE OF SPECIAL IMPORTANCE DUE TO TWO DIFFERENT REASONS; 1) ATTRACTIVENESS OF MULTIMEDIA CONTENTS AND 2) GROWING RATE OF THE CREATION AND ONLINE DISSEMINATION OF SUCH CONTENTS. IN THIS PAPER EVERY EFFORT IS MADE TO ANALYZE AND RECOGNIZE THE PROPENSITIES OF THE USERS OF PERSIAN MULTIMEDIA SEARCH SERVICES. FOR THIS PURPOSE, BEHAVIORS OF IRANIAN USERS OF PARSIJOO’S IMAGE, VOICE AND VIDEO SEARCH SERVICES HAS BEEN STUDIED BY ANALYZING ITS USAGE LOG FILES. THE ANALYSES, WHICH HAVE BEEN CARRIED OUT BY USING USERS’ QUERIES FOR A TIME PERIOD OF THREE MONTHS, CAN BE CATEGORIZED INTO TWO DISTINCT TYPES; HOLISTIC ANALYSES AND THE ONES BASED ON USING FREQUENTLY USED QUERIES. THE RESULTS OF THE ANALYSES HAVE SHOWN THAT USERS ARE MOSTLY AFTER ENTERTAINMENTS AND AMUSEMENT TOPICS WHEN THEY USE MULTIMEDIA SEARCH SERVICES.

ALTHOUGH RECENT STUDIES HAVE PROVIDED A FRAMEWORK FOR DETERMINING FACTORS HELPING ONLINE RETAILERS' SUCCESS, THEY HAVE NOT BEEN OF MUCH SUCCESS IN RECOGNIZING THAT CUSTOMER DECISION-MAKING PROCESS IS MOSTLY INFLUENCED BY INTERNAL FACTORS OF THE WEBSITES (E.G., NAVIGATION, COLOR AND GRAPHICS). ALTHOUGH WEBSITE QUALITY IS IMPORTANT, IT PROVIDES ONLY A SUBSET OF THE EVALUATION CRITERIA OF ONLINE AND POTENTIAL SERVICE PROVIDER. OTHER FEATURES OF ONLINE RETAILERS CAN PLAY IMPORTANT ROLES IN INFLUENCING CUSTOMER'S RESPONSE. THIS STUDY CONSIDERS EXTERNAL (I.E. REPUTATION) AND INTERNAL INFORMATION (I.E. QUALITY OF THE WEBSITE) AS A STIMULANT AFFECTING THE CUSTOMER'S OPINION ABOUT THE WEBSITE OF COMPANIES OFFERING BROADBAND SERVICES IN IRAN. STRUCTURAL EQUATION MODELING (SEM) WAS USED FOR DATA ANALYSIS. THE FINDINGS SHOW THAT SECURITY AND CONFIDENTIALITY HAVE A SIGNIFICANT AND POSITIVE IMPACT ON REPUTATION. MOREOVER, WEB DESIGN AND CUSTOMER SERVICES HAVE A SIGNIFICANT POSITIVE EFFECT ON POSITIVE EMOTIONS OF THE CUSTOMERS. IN ADDITION, WE FOUND THAT SECURITY AND CONFIDENTIALITY HAVE A SIGNIFICANT POSITIVE EFFECT ON SENSIBLE RISK, AND POSITIVE EMOTIONS HAVE A SIGNIFICANT POSITIVE EFFECT PURCHASE INTENTION. FINALLY, SENSIBLE RISK HAS A POSITIVE IMPACT ON NEGATIVE EMOTIONS.

TODAY, MUCH MORE THAN IN THE PAST ARE DISCUSSED OF PLAGIARISM IN THE RESEARCH. CONDITIONS OF THE WEB AND POSSIBILITY OF COMPLEX AND SMART SEARCHES IN A SHORT TIME, IS RATED TO THIS, AND AS A RESULT HAS ARRIVED SIGNIFICANT DAMAGES TO THE RESEARCH. TOOLS DESIGNED TO DEAL WITH PLAGIARISM ACT ON THE TEXT AND IGNORE IMAGES. ON THE OTHER, AN INSEPARABLE PART OF INFORMATION TRANSFER ARE IMAGES THAT TRANSFER THE LARGE VOLUME OF INFORMATION IN AN ARTICLE OR SCIENTIFIC RESEARCH. BECAUSE OF THE IMAGES INCLUDE A VERY WIDE RANGE AND ESPECIALLY FOUND LARGE AMOUNTS OF FLOWCHART IMAGES IN THE COMPUTER'S TEXTS, AND AS RESPECTS, FLOWCHARTS ARE CARRYING A LOT OF INFORMATION, COULD BE ONE OF THE OPTIONS OF PLAGIARISM. THE PURPOSE OF THIS PAPER IS EXAMINE THE PLAGIARISM RATE OF A PAPER IN TERMS OF FLOWCHART IMAGES PLAGIARISM USING ARTIFICIAL NEURAL NETWORK. THE AVERAGE OF FLOWCHART IMAGES RECOGNITION ACCURACY IN TERMS OF STRUCTURE, NODES AND EDGES IN THE PROPOSED METHOD WITH 81.91 PERCENT, INDICATING THE SUCCESS OF THIS METHOD.

THE INCREASING VOLUME OF INFORMATION ABOUT GOODS AND SERVICES HAS BEEN GROWING CONFUSION FOR ONLINE BUYERS IN CYBERSPACE AND THIS PROBLEM STILL CONTINUES. ONE OF THE MOST IMPORTANT WAYS TO DEAL WITH THE INFORMATION OVERLOAD IS USING A SYSTEM CALLED RECOMMENDER SYSTEM. THE TASK OF A RECOMMENDER SYSTEM IS TO OFFER THE MOST APPROPRIATE AND THE NEAREST PRODUCT TO THE USER'S DEMANDS AND NEEDS. IN THIS SYSTEM, ONE OF THE MAIN PROBLEMS IS THE COLD START CHALLENGE. THIS PROBLEM OCCURS WHEN A NEW USER LOGS ON AND BECAUSE THERE IS NO SUFFICIENT INFORMATION AVAILABLE IN THE SYSTEM FROM THE USER, THE SYSTEM WON’T BE ABLE TO PROVIDE APPROPRIATE RECOMMENDATION AND THE SYSTEM ERROR WILL RISE. IN THIS PAPER, WE PROPOSE TO USE A NEW MEASUREMENT CALLED OPINION LEADERS TO ALLEVIATE THIS PROBLEM. OPINION LEADER IS A PERSON THAT HIS OPINION HAS AN IMPACT ON THE TARGET USER. AS A RESULT, IN THE CASE OF A NEW USER LOGGING IN AND THE USER – ITEM’S MATRIX SPARSENESS, WE CAN USE THE OPINION OF OPINION LEADERS TO OFFER THE APPROPRIATE RECOMMENDATION FOR NEW USERS AND THEREBY INCREASE THE ACCURACY OF THE RECOMMENDER SYSTEM. THE RESULTS OF SEVERAL CONDUCTED TESTS SHOWED THAT OPINION LEADERS COMBINED WITH RECOMMENDER SYSTEMS WILL EFFECTIVELY REDUCE THE RECOMMENDATION ERRORS.

DESPITE THE INCREASING USE OF INTERNET BY IRANIANS, THE BOUNCE RATES OF THE E-COMMERCE WEBSITES ARE STILL HIGH. THIS IS BECAUSE THE E-COMMERCE INSTITUTIONS ARE NOT FAMILIAR WITH DESIGNING WEBSITES BASED ON THEIR OWN TARGET MARKET PREFERENCES. SO THE PURPOSE OF THIS PAPER IS TO IDENTIFY AND TO EVALUATE THE EFFECTIVE VISUAL FACTORS FOR ATTRACTING ONLINE USERS.THIS STUDY HAS BEEN CONDUCTED BY AN ATTITUDE ASSESSMENT THROUGH AN ONLINE USER QUESTIONNAIRE TO COLLECT DEMOGRAPHIC DATA THAT INFLUENCE THE USER’S COLOR PREFERENCES AND INTERESTS. NEXT, STATISTICAL ANALYSIS WAS DONE THROUGH A VARIETY OF TESTS INCLUDING T-TEST, ANOVA-TEST AND DUNCAN-TEST. THESE TESTS ARE EMPLOYED TO FIND THE RELATIONSHIP BETWEEN USER'S DEMOGRAPHIC FEATURES AND HIS/HER PREFERRED COLOR ON WEBSITES. THE RESULTS OF THIS STUDY CAN BE USEFUL TO PERSONALIZE THE WEBSITES EXPLOITING THE EXTRACTED RULES OF COLORS.

CLOUD COMPUTING DATA CENTERS OFFER HIGH AVAILABLE AND RELIABLE INFRASTRUCTURES FOR HOSTING CRITICAL APPLICATIONS AND DATA. THESE DATA CENTERS HOST HUNDREDS OF THOUSANDS PHYSICAL MACHINES TO RESPONSE TO INCOMING WORKLOAD AS JOB EXECUTING. IN THIS PAPER, WE ANALYZE THE GOOGLE CLOUD CLUSTER PROPERTIES TO INVESTIGATE THE RELATIONSHIP AMONG MACHINE FAILURES, UPDATES, AND JOB FAILURES. WE PRESENT THE STATISTICAL PROPERTIES OF GOOGLE MACHINES AND JOB FAILURES AND ATTEMPT TO CORRELATE THEM DURING A 29-DAY PERIOD BEHAVE. WE CLASSIFY THE MACHINE AND JOB FAILURES PER DAY AND REPRESENT A RELIABILITY MODEL FOR GOOGLE CLUSTER MACHINES USING THE CONTINUES TIME MARKOV CHAINS.

THIS PAPER PRESENTS A PRACTICAL STUDY OF THE PERSIAN ONTOLOGY MATCHING. ONTOLOGY MATCHING HAS A KEY ROLE TO DEVELOP THE SEMANTIC WEB. ALTHOUGH MANY ATTEMPTS ARE DONE TO DEVELOP PERSIAN ONTOLOGIES, BUT THE PERSIAN ONTOLOGY MATCHING PROBLEM IS STILL UNRESOLVED. THIS PAPER ADDRESSES THE CHALLENGES OF THE PERSIAN ONTOLOGY MATCHING. ONE OF THE MOST IMPORTANT PREREQUISITES OF DESIGN AND DEVELOP EFFICIENT ONTOLOGY MATCHERS IS STANDARD BENCHMARK DATASETS THAT ALLOW A FAIR EVALUATION AND COMPARISON BETWEEN DIFFERENT MATCHERS. FIRST, WE GENERATED A BENCHMARK DATASET FOR PERSIAN ONTOLOGY MATCHING THAT WE NAMED IT PERSIANFARM. PERSIANFARM IS DEVELOPED ACCORDING TO ONTOFARM, THE MULTILINGUAL DATASET OF THE ONTOLOGY ALIGNMENT EVALUATION INITIATIVE (OAEI). IT CONSISTS OF SEVEN PERSIAN ONTOLOGIES AND ELEVEN REFERENCE ALIGNMENTS BETWEEN THEM. NEXT, WE EVALUATE A WIDE RANGE OF SIMILARITY METRICS SUCH AS STRING BASED, STRUCTURAL AND CONTEXT-BASED SIMILARITIES AGAINST PERSIANFARM DATASET. FINALLY, DIFFERENT SIMILARITY METRICS HAVE BEEN SELECTED AND COMBINED TO DEVELOP AN APPROPRIATE PERSIAN ONTOLOGY MATCHER. THE RESULTS THAT REPORTED AS F-MEASURE RATE, SHOW THAT THE MIXTURE OF SIMILARITIES ACHIEVED REASONABLE RESULTS TO MATCH THE CONCEPTS.

PROCESS MODELING IS A SUITABLE TOOL FOR IMPROVING THE BUSINESS PROCESSES. SUCCESSFUL PROCESS MODELING STRONGLY DEPENDS ON CORRECT REQUIREMENTS ENGINEERING. IN THIS PAPER, WE PROPOSED A COMBINATION APPROACH FOR REQUIREMENTS ELICITATION FOR DEVELOPING BUSINESS MODELS. TO DO THIS, BORE (BUSINESS-ORIENTED REQUIREMENTS ENGINEERING) METHOD IS UTILIZED AS THE BASE OF OUR WORK AND IT IS ENRICHED BY THE IMPORTANT FEATURES OF THE BDD (BUSINESS-DRIVEN DEVELOPMENT) METHOD, IN ORDER TO MAKE THE PROPOSED APPROACH APPROPRIATE FOR MODELING THE MORE COMPLEX PROCESSES. AS THE MAIN RESULT, OUR METHOD EVENTUATES IN EXACT REQUIREMENTS ELICITATION THAT ADAPTS THE CUSTOMERS’ NEEDS. ALSO, IT LET US AVOID ANY REWORK IN THE MODELING OF PROCESS. IN THIS PAPER, WE CONDUCT A CASE STUDY FOR THE PAPER SUBMISSION AND PUBLICATION SYSTEM OF A JOURNAL. THE RESULTS OF THIS STUDY NOT ONLY GIVE A GOOD EXPERIENCE OF REAL WORLD APPLICATION OF PROPOSED APPROACH ON A WEB-BASED SYSTEM, ALSO IT APPROVES THE PROFICIENCY OF THIS APPROACH FOR MODELING THE COMPLEX SYSTEMS WITH MANY SUB-PROCESSES AND COMPLICATED RELATIONSHIPS.