An Events Detection and Analysis Using Block Matching With Linguistic Technique

International Journal of Computer Science (IJCS Journal) Published by SK Research Group of Companies (SKRGC) Scholarly Peer Reviewed Research Journals

Format: Volume 6, Issue 1, No 02, 2018

Copyright: All Rights Reserved ©2018

Year of Publication: 2018

Author: V.Geetha#1, Dr.M.V.Srinath*2, P.Aruna*3

Reference:IJCS-333

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Abstract

With the staggering volume of online news accessible today, there is an expanding requirement for programmed systems to examine and show news to the client on an important and productive way. Past look into concentrated just on arranging news stories by their themes into a level progression. A think seeing a news point as a level accumulation of stories is excessively prohibitive and wasteful for a client to comprehend the theme rapidly. An emergency event can happen at any time. So the latent user may not analyze the event and release the news through web source. This may happen only because of proper analyze of the particular event. Since the existing system does not provide the exact news to publish through the website, the thesis proposed a block matching with linguistic technique to analyze and release the particular news event. This may cause the web resources which is based on the different event is developed in order to let the people know of an emergency event clearly and help the social group or government to process the emergency events effectively. The underlying condition of the idle state can be utilized to pronounce the underlying status of the crisis occasion. The trial result demonstrates that dissect will be utilized to settle on the right choice for the client. Index Terms— Topic detection, latent user, block matching with linguistic technique I. INTRODUCTION Presently multi days all news diverts distributed their news in electronic forms too. Clients of online news are expanding quickly because of pool of time for perusing printed copy of daily papers. Proposals news additionally is accessible on different web crawlers and they will refresh the ongoing occasions when they happened: Refreshing news straight away is the real issue and heaps of research is consistently performed in this field. Be that as it may, it likewise creates colossal volume of news content stream. Overseeing deciphering, and breaking down such a colossal volume of data is a troublesome undertaking. Procedures that are fit for removing the hidden structure of the news occasions are wanted. They are useful for the client to comprehend the development of occasions on a similar point. Occasion is something that occurs at some particular time. Despite the fact that client can catch the significant occasions. There are few methods display for occasion assessment, this research concentrated on Topic Detection and following. Topic Detection and following are utilized to find point insightful information and the data is gathered from different sources and might be from various dialects The Topic Detection and following procedure have been endeavoring to identifying or bunching news stories into these occasions, without characterizing or translating the relationship between these occasions. To display the advancement procedure of occurrence, should demonstrate this sort of relationship between occasions, which it characterize as occasion developments [8]. This research concentrated on every single significant segment of occasion assessment and demonstrates the future bearing in this field. Because of the fame of the Internet, most news stories have electronic forms distributed on newswires. Recovering news of a similar theme from various sources and keeping data refreshed turns out to be more advantageous and simpler. Procedures that are fit for removing the fundamental structure of the news occasions are wanted. They are useful to comprehend the advancement of occasions on a similar point. The most imperative undertaking in our proposed framework is to develop the occasion advancement diagram for recognizing the occasion development connections from the occasions. Topic Detection and following is utilized to recognize subjects and following all vital data identified with it. News web recordings are principally made out of visual and literary data. Visual data contains semantic hole and client subjectivity issues, and along these lines, utilizing either visual or literary data alone for news web video occasion mining may prompt unsuitable outcomes. With a specific end goal to beat these deficiencies, both visual and printed highlights are used for web news video occasion mining. For visual data, some essential shots are much of the time embedded into recordings as a help of perspectives, which convey valuable data. Since there is remarkable part of close copy key casings (NDK) in the news look, theme discovery and following (Topic Detection and following) and copyright encroachment identification, these copy key edges/shots are bunched to shape diverse gatherings as indicated by visual substance. Such gatherings are like the hot terms in the content field. Here, each bunch is called a NDK gathering, which can be utilized to aggregate recordings with comparable substance to similar occasions. This research presents an auxiliary displaying approach for maritime submerged fighting, which has been acquired from our improvement of military reenactment show. The presented displaying plan gives the essential of an extendable, adaptable and profoundly reconfigurable recreation system. To accomplish these requirements, we, in the first place, presents a hypothetical premise of the discrete occasion reenactment (DES) demonstrating for maritime submerged fighting. A short time later, proposes a DES-based general model structure and non specific portrayal of the battle substance display[2]. In detail, characterize the battle element display into stage and weapon models and make six gatherings of element models ordered by two measurements: three-capacity and two-deliberation. This gathering empowers us to reconfigure the battle substance show by having a similar interface inside the gathering, and a similar interface turns into the major premise of the adaptable and extendable model piece. At last, expect that this work will serve a quick application for maritime submerged fighting suited to different commitment conditions. Theme Detection and Tracking is an exploration program examining techniques for consequently sorting out news stories by the occasions that they talk about [2]. Topic Detection and following incorporates a few assessment errands, everyone of which investigates one part of that association {i.e., part a persistent stream of news into stories that are about a solitary point ("division"), gathering stories into bunches that each talk about a solitary theme ("discovery"), distinguishing the beginning of another subject in the news, and misusing client criticism to screen a flood of news for extra stories on a predefined subject ("following"). Another Topic Detection and following assessment assignment, Link Detection, requires deciding if two haphazardly chose stories talk about a similar point. Not at all like alternate errands that have an incentive all by themselves, Link Detection is a part innovation: it can be utilized to address everyone of alternate undertakings. II. BACKGROUND For the most part, data mining (once in a while called information or learning revelation) is the way toward dissecting information from alternate points of view and outlining it helpful data - data that can be utilized to expand income, cuts costs, or both. Information mining programming is one of various logical devices for breaking down information. It enables clients to dissect information from a wide range of measurements or points, arrange it and condense the connections distinguished [7]. In fact, information mining is the way toward discovering connections or examples among many fields in expansive social databases. Amid the blast of the microcomputer business and particularly amid the 1980s, clients began to send PCs all over the place by and large with next to zero think about working prerequisites. Be that as it may, data innovation (IT) tasks began to develop in many-sided quality, associations became mindful of the need to control IT assets. The appearance of UNIX from the mid 1970s prompted the ensuing multiplication of uninhibitedly accessible Linux-good PC working frameworks amid the 1990s. These were called "servers" as timesharing working frameworks like UNIX depend vigorously on the customer server model to encourage sharing interesting assets between numerous clients. The accessibility of modest systems administration hardware, combined with new benchmarks for arrange organized cabling, made it conceivable to utilize a progressive outline that put the servers in a particular room inside the organization. The utilization of the expression "server farm" as connected to uniquely planned PC rooms, began to increase famous acknowledgment about this time[5]. The blast of server farms came amid the website rise of 1997–2000. Organizations required quick Internet availability and constant activity to send frameworks and to set up a nearness on the Internet. Introducing such gear was not reasonable for some littler organizations. Numerous organizations began assembling huge offices called Internet server farms (IDCs), which furnish business customers with a scope of answers for frameworks sending and activity. New advances and practices were intended to deal with the scale and the operational prerequisites of such vast scale activities. These practices in the long run relocated towards the private server farms and were received to a great extent due to their pragmatic outcomes. Server farms for distributed computing are called cloud server farms (CDCs). In any case, these days, the division of these terms has nearly vanished and they are being incorporated into a term "server farm". With an expansion in the take-up of distributed computing, business and government associations examine server farms to a higher degree in regions. For example, security, accessibility, ecological effect and adherence to measures. Models reports from authorize proficient gatherings, for example, the Telecommunications Industry Association, indicate the necessities for server farm plan. Understood operational measurements for server farm accessibility can serve to assess the business effect of a disturbance. Improvement proceeds in operational practice, and furthermore in earth agreeable server farm plan. Server farms normally cost a considerable measure to assemble and to keep up. III. RELATED WORK A.Time series segmentation for context recognition in mobile devices In this research, perceiving the setting of utilization is essential in making cell phones as easy to use as would be prudent. Discovering what the client's circumstance is can encourage the gadget and hidden administration in giving a versatile and customized UI. The gadget can induce parts of setting of the client from sensor information: the cell phone can incorporate sensors for increasing speed, clamor level, radiance, dampness, and so forth. In this research, consider setting acknowledgment by unsupervised division of time arrangement created by sensors. Dynamic programming can be utilized to find sections that limit the intra-fragment fluctuations. While this technique produces ideal arrangements, it is too moderate for long successions of information. They display and investigate randomized varieties of the calculation. One of them, Global Iterative Replacement or GIR, gives around ideal outcomes in a small amount of the time required by powerful programming. They exhibit the utilization of time arrangement division in setting acknowledgment for cell phone applications. Fruitful human correspondence is normally relevant. They talk about with each other in various routes relying upon where they are, what time it is, who else is near, what has occurred previously, and so forth there is bunches of setting data that is certainly being utilized as a part of regular daily existence. B.Earthquake Shakes Twitter Users: Real-time Event Detection by Social Sensors In this research, the constant idea of Twitter and proposes an occasion notice framework that screens tweets and conveys warning quickly. To acquire tweets on the objective occasion accurately, apply semantic examination of a tweet: For instance, clients may make tweets, for example, "Seismic tremor!" or "Now it is shaking" along these lines quake or shaking could be catchphrases, however clients may likewise make tweets, for example, "I am going to an Earthquake Conference", or "Somebody is shaking hands with my manager". It set up the preparation information and devise a classifier utilizing a help vector machine in light of highlights, for example, watchwords in a tweet, the quantity of words, and the setting of target occasion words. In this way, make a probabilistic spatiotemporal model of an occasion. Its make a pivotal supposition: each Twitter client is viewed as a sensor and each tweet as tactile data. These virtual sensors, which they call social sensors, are of a tremendous assortment and have different qualities: a few sensors are extremely dynamic; others are most certainly not. A sensor could be inoperable or breaking down once in a while (e.g., a client is resting, or caught up with accomplishing something). Thus, social sensors are exceptionally loud contrasted with ordinal physical sensors. With respect to Twitter client as a sensor, the occasion recognition issue can be diminished into the question identification and area estimation issue in an omnipresent/inescapable registering condition in which they have various area sensors: a client has a cell phone or a functioning identification in a domain where sensors are set. Through infrared correspondence or a Wi-Fi flag, the client area is evaluated as giving area based administrations, for example, route and historical center aides. Apply Kalman channels and molecule channels, which are generally utilized for area estimation in omnipresent/unavoidable registering. C.A Method to Facilitate Uncertainty Analysis in LCAs of Buildings Francesco This research aims to search the effect of suspicions on information circulation on the aftereffects of vulnerability investigation and to give an imaginative straightforward way to deal with lessen the multifaceted nature of the evaluation and tedious information accumulation exercises. It depends on vigorous essential information gathered from European assembling plants identified with the glass and development industry. (The nature of the information is exhibited by the family lattice, for the information are portrayed by the accompanying scores over the important five markers which are: Reliability, Completeness, Temporal Correlation, Geographical Correlation, Further Technological Correlation where (1) is the most noteworthy conceivable score and (5) is the least, accepted as the default esteem. The calculation has additionally been tried on haphazardly produced information and it works similarly fine. The central part of vulnerability examination in LCAs is effortlessly comprehended by looking. The figure demonstrates a ridicule illustration where the encapsulated vitality (EE) of two choices, 1 and 2, are being thought about. Most LCAs just give deterministic, single-esteemed outcomes which for the most part speak to the undoubtedly esteems coming about because of the particular life cycle stock (LCI) being considered. These qualities can be viewed as m1 and m2 in the figure. On the off chance that a choice were to be taken just in light of such numbers one ought to reason that elective 1 is ideal over elective 2 since m1 is lower than m2. The correlation between these two options, and their effect on the vulnerability of the aftereffect of the LCA, was the supporting thought for this exploration. D.Crowdsourcing-based Disaster Management using Fog Computing in Internet of Things Paradigm In this research, with the point of taking the upsides of crowdsourcing and haze processing to deal with debacle administration in a proficient way, propose a crowdsourcing based disaster management using fog computing (CDMFC) display in IoT. Further, an information offloading the component is proposed for our CDMFC demonstrate if an immediate connect to the mist isn't accessible considering the poor correspondence foundation amid the calamity time. Information offloading the instrument in CDMFC show ensures that catastrophe related IoT information is effectively sent to the haze. When contrasted with the customary distributed computing based calamity administration models, our proposed CDMFC model can recognize continuous fiascos and spread early data for open wellbeing. Through crowdsourcing and information offloading component, the group sourced basic catastrophe related IoT information is examined in CDMFC layer distributed as are taking focal points of haze registering. Here, the group sourced basic information is dissected continuously and it limits inertness dissimilar to gigabytes of information are sent to the cloud for examination specifically from crowdsourcing layer. These days, the information are created with time and area stamps. The information created through a different application, for example, Facebook and Twitter gives area and time stamps progressively. CDMFC demonstrate exploits this component to pinpoint the correct area and time of the debacle in a brief timeframe which is constantly urgent when the lives of a large number of people groups are in threat. Further, in our CDMFC display, this layer is outfitted with crisis contact numbers and is specifically available to open security expert who can design safeguard activity and make essential move as per the group sourced basic debacle related IoT information. All the media applications identified with calamities. For example, video, cuts, photographs and so forth is spared in the haze and individuals of the influenced locale can without much of a stretch see and efficiently understand the present circumstance. In addition, our CDMFC model can monitor arrange transfer speed as the main debacle related information will be investigated on mist and rest of the information will be examined in the cloud. Not at all like distributed computing models which are frequently the objective for aggressors to control the IoT information, CDMFC model can safely work on the IoT information inside the mist where they can introduce of our own lightweight security calculations. E.An Analytical Review of Quality Attributes of Service-Oriented Architecture In this research, availability of administrations is of extraordinary worry for the accomplishment of SOA. It can be seen from two points of view: clients and in addition supplier's viewpoint. From the clients point of view, if the administration isn't accessible, at that point the utilitarian prerequisites of the framework can't be met. Accessibility is characterized as an extent of time when a framework or a segment is open for utilize. Observing the accessibility of administration and satisfaction of nature of-benefit prerequisites. For example, execution are taken care by specialist organizations. Methods like replication and load-adjusting are utilized to expand the accessibility of administrations. Administrations should likewise have worked in possibilities, so they can locate an elective supplier for themselves in the event of inaccessibility of administrations. Yet there is parcel to do with accessibility of possibility instrument inside an administration for its programmed accessibility. In this research, the idea of SOA, a design style for building frameworks alongside its life cycle is clarified. The quality characteristics like interoperability, execution, security, unwavering quality, accessibility, modifiability, testability, ease of use and adaptability are extremely all around clarified alongside their present status and in addition future prerequisites. Future work will center around the investigation of administration level assertions which help in giving fundamental level of administrations to benefit purchasers. All things considered, an incredible work is required to manage the quality properties and quality necessities in SOA life cycle. IV. METHODOLOGY The web can give related data promptly after a crisis occasion happens and continue refreshing the data in close ongoing, which is a key prerequisite for monitoring the sudden changing nature of a crisis occasion. Customary media, for example, daily papers and magazines can't report a crisis occasion instantly. Interestingly, the web can manage this issue legitimately. As of late, with the quick improvement of the internet based life locales, for example, Twitter and Facebook, the web has turned into a vital occasions data supplier. The speedy and simple spread of data through the web can give a far reaching viewpoint of crisis occasions. Conventional media for the most part gives content that has been substantiated and additionally analysis, for example, master sentiments to general society. As it were, customary media generally endeavors to explore and achieve conclusions identified with various parts of crisis occasions as opposed to just announcing them. Not the same as the conventional media, the web can give alternate points of view of a crisis occasion. Distinctive clients can give their own sentiments around a crisis occasion. The open component of the web guarantees that clients think about the diverse parts of a crisis occasion including the distinctive suppositions/data about the occasion. The dynamic component of web data can stay aware of the advancement of crisis occasions. Obviously, a crisis occasion isn't static and the data about it might change with time. In a few investigations, the changing idea of an occasion is named as "occasion development." This huge measure of data ought to have a proper portrayal and availability to be helpful. Other than the huge volume of information, the data with respect to a crisis occasion refreshes rapidly. An Exact and solid estimation of the state time of a discourse motion from the acoustic weight waveform alone is frequently exceedingly troublesome for a few reasons. One reason is that the glottal excitation waveform is anything but an ideal prepare of intermittent heartbeats. In spite of the fact that finding the time of an impeccably occasional waveform is clear, estimating the time of a discourse waveform, which shifts both in a period and in the nitty gritty structure of the waveform inside a period, can be very troublesome. A second trouble in estimating state period is the collaboration between the vocal tract and the glottal excitation. In a few occurrences the formants of the vocal tract can modify altogether the structure of the glottal waveform with the goal that the real state time frame is hard to distinguish. Such communications by and large are most pernicious to state location amid fast developments of the articulators when the formants are additionally evolving quickly. A third issue in dependably estimating state is the innate trouble in characterizing the correct start and end of each state period amid voiced discourse fragments. The decision of the correct start and consummation areas of the state time frame is frequently very discretionary. The main necessity on such an estimation is, to the point that it be steady from period-to-period with a specific end goal to have the capacity to characterize the "correct" area of the start and end of each state period. The absence of such consistency can prompt fake state period gauges. It indicates two conceivable decisions for characterizing a state marker specifically in light of waveform estimations. The two waveform estimations appeared in model can (and frequently will) give somewhat unique qualities for the state time frame. The state time frame inconsistencies are expected not exclusively to the semi periodicity of the discourse waveform, yet additionally the way that pinnacle estimations are touchy to the formant structure amid the state time frame, while zero intersections of a waveform are delicate to the formants, clamor, and any dc level in the waveform. A fourth trouble in state identification is recognizing unvoiced discourse and low-level voiced discourse. By and large advances between unvoiced discourse portions and low-level voiced discourse fragments are exceptionally inconspicuous and in this way are to a great degree difficult to pinpoint. Input: Blog news, Output: Fake News Detection for all horizontal strict local maxima do x ← first coordinate of strict local maximum vote x [x mod 8] ++ end for for all vertical strict local maxima do y ← second coordinate of strict local maximum vote y [y mod 8] ++ end for n_x, n_y ← sum(vote x), sum(vote y): total number of local maxima horizontal, vertical k_x, k_y ← max(vote x), max(vote y): number of votes of the elected coordinates. Theoretical research and broad reproductions have been led to assess our plan. The aftereffects of LBS show that our proposed plot is more secure and vitality proficient is a best in class secure various leveled in-organize conglomeration conspire proposed. This is on the grounds that information transmissions contribute the significant bit of the power utilization for sensor hubs, and the correspondence overhead of Existing Methods is higher than that of MAI as examined previously. Since the vitality utilization is firmly identified with the correspondence overhead, our outcomes demonstrate a general pattern of expanding with expanding the system estimate, with a few variances at a few focuses. In the rundown, the hypothetical and recreation comes about both demonstrate that our proposed more proficient and viable than Existing Methods, as it can distinguish the noxious aggregators with a much lower correspondence overhead by guaranteeing high Security. V. RESULT AND DISCUSSION In our analyses, the flare-up intensity of every occasion is worked from three data sources including news, blog and talk. The episode control is distinctive for the three data sources. In the event that I set the episode intensity of every data source as a vector, at that point I can figure the cosine-likeness of these data sources. The similitude amongst online journals and talk is higher than that of news and exchanges. This outcome might be caused by the social sensors of these data sources. The social sensors of blog and dialog are web clients. Then again, the social sensors of news are editors or journalists. From the analysis discoveries on the genuine information, realize that the proposed calculation can recognize diverse conditions of an occasion precisely. The data from the web can be incorporated into processing episode power and variance control. These two elements can be utilized to distinguish conditions of a crisis occasion. Other than the investigation of trial comes about, some other intriguing highlights can be gathered from the examination, which is talked about in the following area. I have exhibited another point of view of displaying news subjects. As opposed to the method perspective of points as level accumulation of news stories, see a news subject as a social structure of occasions interconnected by conditions. In this examination, proposed a couple of methodologies for both bunching stories into occasions and developing conditions among them. A built up a period rot based bunching approach that exploits transient restriction of news stories on a similar occasion and demonstrated that it performs essentially the superior to anything the gauge approach in view of cosine closeness. Our investigations likewise demonstrate that can do genuinely well on conditions utilizing just surface-highlights, for example, cosine comparability and time-stamps of news stories insofar as evident occasions are given to the framework. In any case, the execution break down quickly if the framework needs to find the occasions independent from anyone else. Notwithstanding that debilitating outcome, have demonstrated that our joined calculations perform altogether superior to the baselines. In experiment result, conducted using proposed methodology to find the performance evaluation and error rate to compare with existing approach. VI. CONCLUSIONS This exploration work proposed a novel calculation to identify the diverse states utilizing the square coordinating occasions gave an account of the web. To begin with, the related assets including pages, catchphrases of a crisis occasion are gathered utilizing web search tools. Second, the flare-up control and the variance intensity of a crisis occasion at various timestamps are registered. In light of the different transient qualities, distinctive conditions of a crisis occasion are recognized. Future work will incorporate stretching out our way to deal with different applications, for example, hot news investigation with the points of further approval and refinement. The worldly highlights of the crisis occasion imaged on the web are characterized, which coordinate the quantity of expanded website pages, the quantity of expanded catchphrases, the circulation of watchwords, and the connections between watchwords. Furthermore, some heuristic standards are given to recognize the diverse conditions of a crisis occasion. Analyses utilizing genuine informational collections (genuine web occasions) exhibit the astounding execution of the proposed calculation and confirm its viability and vigor. The proposed calculation can encourage a social gathering or governments process the crisis occasions and let the general population think around a crisis occasion methodicallly. The proposed occasion development chart is utilized to exhibit the fundamental structure of the occasions.

References

[1] Y. Jo, C. Lagoze, C. Lee Giles. Detecting research topics via the correlation between graphs and texts. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 370-379, 2007.
[2] R. Nallapati, A. Feng, F. Peng, and J. Allan. Event threading within news topics. In Proceedings of the thirteenth ACM international conference on Information and knowledge management, pp. 446-453, 2004.
[3] G. Salton and C. Buckley. Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5):513-523, 1988.
[4] X. Jin, S. Spangler, R. Ma, and J. Han. Topic Initiator Detection on the World Wide Web. In Proceedings of the 19th international conference on World Wide Web, pp. 481-490, 2010.
[5] X. Yin, J. Han, and Philip S. Yu. Truth Discovery with Multiple Conflicting Information Providers on the Web. IEEE transaction on knowledge and data engineering, 20(6):796-808, 2008.
[6] E. Keogh, K. Chakrabarti, M. Pazzini, and S. Mehrotra. Dimensionality reduction for fast similarity search in large time series databases. Journal of Knowledge and information systems, 3(3), 2000.
[7] J. Allan, G. Carbonell, G. Doddington, J. Yamron, and Y.Yang. Topic Detection and Tracking Pilot Study Final Report. In Proceedings of the Broadcast News Transcription and Understanding Workshop, 1998.
[8] J. Allan. Topic Detection and Tracking: Event-Based Information Organization. Norwell, MA: Kluwer, 2000.
[9] Q. Mei and C. Zhai. Discovering evolutionary theme patterns from text: An exploration of temporal text mining. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, pp.198-207, 2005.
[10] F. Jess, M. Trina, T. Jarrod, et al. Riskr: A lowtechnological Web2.0 disaster service to monitor and share information. In the Proceedings of 15th International Conference on Network-Based Information Systems, pp. 1-8, 2012.
[11] J. Makkonen. Investigation on event evolution in TDT. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language, PP.43-48, 2003.
[12] C. Yang, X. Shi, and C. Wei. Discovering Event Evolution Graphs from News Corpora. IEEE Trans. on Systems, Man and Cybernetics—Part A: 39(4):850-863, 2009.
[13] J. Abonyi, B. Feil, S. Nemeth, and P. Arva. Modified Gath–Geva clustering for fuzzing segmentation of multivariate timeseries. Fuzzy Sets and Systems, Data Mining, Special Issue 149:39-56, 2005.
[14] X. Wu, Y. Lu, Q. Peng, and C. Ngo. Mining Event Structures from Web Videos. IEEE Multimedia, 18(1):38-51, 2011.
[15] Q. He, K. Chang, E. Lim and A. Banerjee. Keep It Simple with Time: A Reexamination of Probabilistic Topic Detection Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(10):1795-1808, 2010.
[16] C. Sung and T. Kim Collaborative Modeling Process for Development of Domain-Specific Discrete Event Simulation Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 42(4):532-546, 2012.
[17] C. Wei and Y. Chang. Discovering event evolution patterns from document sequences. IEEE
Transactions on Systems, Man and Cybernetics, Part A, 37(2):273–283, 2007.
[18] C. Yang and X. Shi. Discovering event evolution graphs from newswires. In Proceedings of the 15th international conference on World Wide Web, pp. 945-946, 2006.


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