Web Portal Essay Example

Web Portal Essay Automatic Identification of Temporal Information in Tourism Web Pages Stephanie Weiser*, Philippe Laublet**, Jean-Luc Minel* * MoDyCo, UMR 7114, CNRS 200 avenue de la Republique, 92001 Nanterre ** LaLIC, Universite Paris-Sorbonne Maison de la recherche, 28 rue Serpente 75006 Paris E-mail: steph. [emailprotected] com, Philippe. [emailprotected] fr, [emailprotected] fr Abstract This paper presents our work on the detection of temporal information in web pages. The pages examined within the scope of this study were taken from the tourism sector and the temporal information in question is thus particular to this area.The differences that exist between extraction from plain textual data and extraction from the web are brought to light. These differences mainly concern the spatial arrangement of the text, the use of punctuation and the respect of traditional syntactic rules. The temporal expressions to be extracted are classified into two kinds: temporal information that concerns one parti cular event and repetitive temporal information. We adopt a symbolic approach relying on patterns and rules for the detection, extraction and annotation of temporal expressions; our method is based on the use of transducers.First evaluations have shown promising results. Since the visual structure of a web page is very important and often informs the user before he has even read the text, a semiotic study is also presented in this paper. 1. Introduction With the methods of the Semantic Web, portal applications can be created, relying on ontologies. For these applications and many service applications, temporal information is often essential. For example, a tourism web portal would need information about the type of tourism object and its location in time and space.In addition, the extracted information must be stored in the knowledge base according to the ontology used by the application. In this paper we will focus on temporal information in tourism web pages. The temporal informat ion has to be detected, extracted and annotated. The annotation format will probably rely on existing XML tools (Stern 2007). To perform these tasks, we encountered three main kinds of difficulties. First, we have to deal with complex, imprecise temporal information. Of course, single dates are easy to process but more complex expressions, such as periods or repetitive information (e. . from March to July, open every day except Tuesday), must be treated as well. Second, after being extracted, the information needs to be linked to the proper tourism object. If the web page concerns only one object, this is straightforward, but some web pages concern many objects and an analysis is therefore necessary to decide how to link each piece of information to its object. Third, the web pages we deal with are all of the same type: tourism web pages. However, they vary a lot as they are made by different people, have different forms and concern different types of tourism objects.We will try to show that a semiotic study of some pages is necessary to take into account some of their specificities. The work presented in this paper is situated within the framework of the EIFFEL project. Its main objective is to create a portal in the area of tourism with different functionalities. This portal, for use by the local tourism sector, will include a specialised search engine. It will allow users to find and collect precise and essential information in context. It will also help the territory as a French region to promote its services. This is a wideranging project (Noel et al. 008) which is based on web semantic technologies, knowledge representation and linguistic methods and expertise. It includes automatic identification, selection and extraction of various items from the Web according to existing ontologies. This project involves mainly two companies – Mondeca and Antidot – and three laboratories – LIRMM (CNRS), INRIA-Rocquencourt and MoDyCo (CNRS). Our co rpus, meaning that the pages have been collected for this particular study, in a precise context, is composed of more than 5000 tourism web pages in French. These pages were collected by automatic crawling of websites.They were collected by the company Antidot and transformed into XML files in order to make them more suitable for automatic processing. 2. Temporal Information in Web Pages The detection and extraction of temporal information is a subject that has already been widely studied (Battistelli et al. 2006), but mostly in the context of â€Å"printed textual objects† and not in texts specifically written for web pages. One of the aims of this paper is to show that studying the same type of temporal information is very different when it takes place in a web context.In tourist guide books, for example, the information is a lot more structured and standardized than on our web sites, which are extremely diverse and do not follow a 127 common page model. Every entry of a gu ide concerning a particular tourism object is often structured in the same way and contains the same type of information. Linguistic markers allow us to locate each piece of information. Punctuation is very rigorous and facilitates interpretation, especially automatic interpretation. On the other hand, on web pages, punctuation – if there is any – is rarely correctly used.More often, white spaces or new lines are used as separators. Even if the analysis of a text is not easy, a lot of syntactic tools already exist to perform this task automatically. For example, it is possible to build the syntactic tree of a given sentence, find the verb, etc. However, some complicated tasks, such as anaphora resolution, can make the analysis of texts a lot more complex. What we are interested in here is that the difficulties that are encountered for web pages are very different from those that text analysis presents.For example, in a tourism guide book1, each restaurant entry is stru ctured in the same way: name, address, phone number, metro station and opening details, e. g. ouvert tous les jours (open every day). Each item can easily be automatically processed. The problem is that, on a web page, the same kind of information would more likely look like the web page presented in figure 1. integrating temporal and spatial reasoning into XML query and transformation operations. Their work has lead to WebCal, a program which provides calendrical calculations for web services. 3. Tool and Method for the Temporal Expression DetectionWe have a symbolic approach relying on patterns and rules for the detection, extraction and annotation of temporal expressions (in French). We do not use any machine learning techniques. Our method relies on the use of transducers, created using the graphical interface of the Unitex corpus processor2. Unitex provides an intuitive and user-friendly method for creating transducers, which tag the output (as opposed to regular expressions wh ich do not modify the output). A wide variety of patterns can be recognized and tagged by our transducers, from very simple expressions to very complex ones.On one hand, generalizations can be made (such as using the symbol to tag all numbers). On the other hand, the transducers can be very detailed and precise for particular cases, for example, to recognize expressions such as a lexception du mois de mai – except in May. Here are a few examples of the expressions to be detected: (1) Le 21 avril April, the 21st (2) Du 10 au 21 mars From the 10th to the 21st of March (3) Du lundi au vendredi, 9h – 11h From Monday to Friday, 9am-11am (4) Inauguration du musee le 7 juillet 2006 Inauguration of the museum on the 7th of July 2006 (5) En Juillet et Aout ouvert tous les jours.Hors cette periode, fermeture le mercredi soir, le jeudi toute la journee et le dimanche soir. Horaires douverture: de 12h00 a 14h00 de 19h00 a 22h00. Open every day in July and August. Outside this peri od, closed on Wednesday night, all day Thursday and on Sunday night. Opening times: from noon to 2pm from 7pm to 10pm. Figure 1: Example For now, there is no tool able to interpret that Chez Paul et Bernadette Colas is the name of a Bed Breakfast or that Ouvert du 15 fevrier au 30 (open from February 15th to 30th) is its opening information.This is why the extraction of temporal information from texts can not be directly applied for Web pages: there is no standardized â€Å"syntax† for web pages. Our work is close to that of (Tenier et al. 2006). The object of their work is to extract, from web pages, information about contributors to scientific events. Our approach is more general since the web pages analyzed by these authors follow spatial arrangement rules while spatial arrangement on our pages is completely free. Our work is also close to that of (Bry et al. 2003) who aim at 1 3. 1. ClassificationAs shown in these examples, the type of temporal information to be identifi ed varies. Two main types can be highlighted: temporal information that concerns one particular event and repetitive temporal information. For the first type there are dates (concert on October 1st), periods (festival from May to June), and times (the concert starts at 8:00). For the second there are times (the museum opens at 10am), periods (the restaurant is open from Monday to Saturday) and exceptions (the camping ground is open all year long except in January). More complex examples, such as from MarchLe guide du routard – Paris balades 2007 p. 231 :  « Le SaintAmour 2, av. Gambetta, 75020. 01-47-97-20-15. Metro PereLachaise. Ouvert tous les jours  » (Open every day) 2 Unitex: http://www-igm. univ-mlv. fr/~unitex 128 to July, open every day except Tuesday, can also be included in this classification. In addition, not every occurrence of temporal information needs to be detected, since they do not necessarily concern a tourism object. For example, a single date, which is not introduced by a linguistic marker such as heure douverture (opening time) probably does not concern a tourism object.Single dates like these often concern the web page itself as in Derniere modification : 25/10/2006 (last modification : 25/10/2006). Therefore, we have been careful not to detect these dates. One problem that has been encountered is that some lexical marks are ambiguous. For example is Friday and Sunday night to be interpreted as meaning Friday night and Saturday night, or rather Friday all day and Saturday night? The context is therefore necessary to remove the ambiguity. For this example, if the object is a concert, the first interpretation will probably be the right one.For the whole corpus of 100 pages, we obtain a recall rate of 92% and a precision of 76%. Figure 2: Recall for the first evaluation 3. 2. Technical Information The tool Unitex, which uses dictionaries based on the tables of the LADL3, allows the user to process corpora on the lexical, syntact ic and morphological levels. It allows for the identification and tagging of structures which correspond to regular expressions, represented by finite state graphs. This graphical representation makes using Unitex more intuitive than the use of long regular expressions.We built our transducers using this tool, following the linguistic study that listed the patterns of temporal expressions that could be found on web pages. The set of transducers includes one main transducer and 23 secondary graphs. These transducers include 88 lexical markers (like ouverture – opening, mars – March, inauguration) and 22 grammatical markers (like sur – on, le – the, dans – in). Figure 3: Precision for the first evaluation The important variation in the results is due to the fact that there are not a lot of temporal expressions to detect in the pages (7 for sets 1 and 3, 9 for set 2, 20 for set 4 and 8 for set 5).The precision for set 5 is especially low because one p age contains a forum with 4 temporal expressions that are detected but do not concern a tourism object. 4. Evaluations 4. 1. First Evaluation The transducers allowing the detection of temporal information were manually created from a study of a set of pages. In order to evaluate and optimise them, we tested them on sets of 20 web pages, randomly manually selected from our corpus. This operation was performed five times and the transducers have thus been tested on 100 different pages. The results of this experiment are presented in the diagrams below.Recall and precision were calculated for each set of 20 pages (figure 2 and figure 3). 4. 2. Second Evaluation A different procedure was used for the second evaluation. We deliberately manually selected 25 pages containing temporal information. Some of these pages were randomly opened and selected when they were found to contain temporal information; for the others our transducers were applied to more than 200 pages and those with result s were selected. For these 25 pages, the recall is 39,1% and the precision is 46,5%. Here are a few numbers to explain these figures. These pages contain 69 expressions to detect.The transducers match and tag 58 expressions: 27 are correctly detected, 3 are falsely detected (they should not be detected because they do not correspond to temporal tourism information), 28 expressions are incompletely detected and 25 expressions are missed. We are faced with two kinds of incomplete expressions. In the first kind a part of the expression is not matched, Laboratoire d’Automatique Documentaire et Linguistique – the tables were created by Maurice Gross and consist in a classification of lexical units according to syntactic and distributional criteria. 3 129 or example in toute la journee de 8h00 a 19h00 (all day long from 8:00am to 7:00pm), only the underlined part is detected. In the second kind of incomplete expressions, each pattern to be matched is detected in two or more matches, for example ouvert tous les jours en juillet et aout (open every day in July and August) is detected in two matches. 16 of the 28 incomplete expressions produced by our system correspond in fact to 5 correct expressions. Horaires Lundi Mardi Mercredi Jeudi Vendredi Samedi Matin 8h30-12h00 8h30-12h00 8h30-12h00 8h30-12h00 8h30-12h00 10h00-11h30Ap-midi 14h00-18h00 14h00-18h00 14h00-18h00 14h00-18h00 14h00- Figure 5: vertical table of opening times A human user would understand both of these tables without the slightest problem. For an automatic treatment, however, it is more complicated. If we do not look at the structure, but only at the text, the first table would then contain â€Å"Horaires lundi mardi mercredi jeudi vendredi samedi matin 08h30 12h00 08h30 12h00 08h30 12h00 08h30 12h00 08h30 12h00 10h00 11h30 ap. midi 14h00 18h00 14h00 18h00 14h00 18h00 14h00 18h00 14h00 †: a text flow that is incomprehensible.The second table would contain â€Å"Horaires Matin Ap-midi Lundi 8h30-12h00 14h0018h00 Mardi 8h30-12h00 14h00-18h00 Mercredi 8h3012h00 14h00-18h00 Jeudi 8h30-12h00 14h00-18h00 Vendredi 8h30-12h00 14h00 – Samedi 10h00-11h30 † it is clearer but it is very different from the text of the first one, for exactly the same meaning. Technical tools that allow a specific markup for headers in the table exist. But the web pages of our corpus are mostly built by professionals from the tourism sector and not by professional web designers: they do not use these technical tools.Consequently, only graphical elements and lexical content allow interpretation of these kinds of tables. In order to take into account these semiotic marks in automatic processing, the structure of the pages must be studied. An analysis of the XML tree is therefore necessary (Tenier et al. 2006). The high number of missed expressions is due to the fact that isolated dates without context are voluntarily ignored in order to avoid incorrect detections (li ke in derniere modification : 25 avril 2006 – last modification: April the 25th 2006).Some pages presenting an event schedule contain more than 10 dates without context that are therefore not detected. 22 out of the 25 missed expressions are concerned by this problem, which will be solved in the near future. 5. The Semiotic Marks For now, only textual information is taken into account, but a web page presents information in many other ways. The visual structure of a web page often informs the user before he has even read the text. For example, the structure could allow him to understand that the page concern one single object and not a collection of objects.In the same way, the formatting style (font, size, colour) can be very meaningful since it can often be assumed that two items written in the same font and colour are linked. One difficulty lies in automatically interpreting these semiotic marks. Many things are understandable at first sight for a human being but are hard to specify for automatic processing. On web pages, tables are commonly used to present information. They need a special treatment since their interpretation is not straightforward. 6. Conclusion In this paper we have presented our work on the detection of temporal information in web pages.We have focused on the differences that exist between extraction from plain textual data and extraction from the web. In addition, we introduced our main linguistic resource, our transducers, which could be used for many different NLP applications. We also presented the results obtained in applying these transducers to our corpus. The transducers that have been presented will be improved. They will be enriched with information concerning the type of tourism object, in order to determine the links between the temporal information detected and what they refer to.The work on semiotic marks will be continued in order to implement the study of the structure of the pages, analysing XML trees. Figure 4: O pening times table The figure 4 is an example of a table of opening times found on a web page. The first row contains the names of the days, the second row contains the opening times in the mornings and the last row contains the opening times in the afternoons. The information could have been presented in a vertical table as the one shown in figure 5: 130 7. Acknowledgements The project EIFFEL (ANR-05-RNTL-007) is funded with an ANR grant. .References Battistelli, D. , Minel, J. -L. , Schwer, S. (2006). Representation des expressions calendaires dans les textes : une application a la lecture assistee de biographies, Traitement Automatique des Langues, 47, 3, pp. 126. Bry, F. Lorenz, B. Ohlbach, H. J. Spranger, S. (2003). On Reasoning on Time and Location on the Web, Lecture Notes in Computer Science, Springer-Verlag, Germany, pp. 6983. Noel, L. , Carloni, O. , Moreau, N. , Weiser, S. (2008). Designing a Knowledge-Based Tourism Information System, Int. J. f Digital Culture and Electr onic Tourism, Special Issue on National Tourism Organisations and Exploitation of Information Technologies, to be published. Stern, R. -D. (2007). Expression linguistique du temps et representation ontologique : OWL-Time et etude des adverbiaux temporels, Memoire de Master IILGI, Universite de Paris-Sorbonne. Tenier, S. , Toussaint, Y. , Napoli, A. et Polanco, X. (2006). Instantiation of relations for semantic annotation, In the 2006 IEEE/WIC/ACM International Conference on Web Intelligence WI 2006, pp. 463-472 131

Online Pharmacy Essay Samples - Find Some Great Writing Materials

Online Pharmacy Essay Samples - Find Some Great Writing MaterialsThe best place to start your search for pharmacy essay samples is online. Using a pen and paper, or a laptop computer will help you write an essay in the comfort of your own home. On the internet you can find very detailed samples of essays that have been written for a variety of courses, including pharmacy.When you are filling out the details for your pharmacy syllabus, you can get sample essays to use as templates. They can be arranged in chronological order, and you can change the content of the essay as well as the formatting. You can also change the wordings of the words in the syllabus, and you can include answers that you have written to these questions.Your online bookstore will have a large selection of books and writing samples for you to select from. They should also include essays that are free to download. You can then print the cover page with this text, and this will help you to create your own sample pha rmacy essay.If you do not have access to your library, you can use the Google Docs to create a cover page for your library. When you are done, print it out, and then you can paste the contents of the pharmacy essay sample on top of your book cover.One advantage of using pharmacy essay samples for your school is that you do not have to pay to use the material. In the United States, federal law prohibits schools from charging students for used items. If they do, they must provide a credit.It is highly recommended that you send your own homework assignments, as well as essays, to your professors or tutors. This will help you to give them a more personal touch, and it will give you a better chance of getting a good grade.Whether you are a student at school, or a high school teacher, it is recommended that you purchase all of your writing samples online. The convenience of this method is far greater than any other method.

Image and Reality essays

Image and Reality essays Image and Reality In the years since the thousand days many questions have been raised and are still being studied about John F. Kennedy. A Life of John F. Kennedy: A Question of Character is a book written by Thomas C. Reeves, in which Reeves discusses these issues. JFK was a great man, and yet there are still some things that one must take into consideration. His morality was always somewhat of an uncertainty; be that as it may, these questions are still not openly discussed. People were always taken aback by his personality, good looks, and youth. After his death, it was quite difficult for most people to accept some of the newly discovered negative information about him. The man meant so much to some people that it was impossible to say something less than perfect. But all the same, facts can not be denied. While one may think that each is responsible for his or her actions, that is not always the case. Much of Jacks character develops and originates from his family. He applied these beliefs to his life as well as his presidency. His great grandfather Joseph Kennedys indifference toward people, and the will to do anything to get what he wants, helped to shape much of the character in the entire Kennedy line. Inferior treatment of women also originated from this source. The lacking of a sufficient background as well as a good role model helped shape much of Kennedys negative characteristics. This was reflected in most of his decisions, as a result. So therefore, diversity between Kennedys presidential appearance, and his private life of scandals, was unmistakable. His indifference to the values of proper judgement, unselfishness, and sincerity to his wife and work was also reflected in his ability to make thought out decisions. Though interesting enough, his greatest talent was the ability to manipulate himself well enough that it appeared as though he contained the quali...

Argon Facts (Atomic Number 18 or Ar)

Argon Facts (Atomic Number 18 or Ar) Argon is a noble gas with element symbol Ar and atomic number 18. It is best known for its use as an inert gas and for making plasma globes. Fast Facts: Argon Element Name: ArgonElement Symbol: ArAtomic Number: 18Atomic Weight: 39.948Appearance: Colorless inert gasGroup: Group 18 (Noble Gas)Period: Period 3Discovery: Lord Rayleigh and William Ramsay (1894) Discovery Argon was discovered by Sir William Ramsay and Lord Rayleigh in 1894 (Scotland). Prior to the discovery, Henry Cavendish (1785) suspected some unreactive gas occurred in air. Ramsay and Rayleigh isolated argon by removing the nitrogen, oxygen, water, and carbon dioxide. They found the remaining gas was 0.5% lighter than nitrogen. The emission spectrum of the gas did not match that of any known element. Electron Configuration [Ne] 3s2 3p6 Word Origin The word argon comes from the Greek word argos, which means inactive or lazy. This refers to the extremely low chemical reactivity of argon. Isotopes There are 22 known isotopes of argon ranging from Ar-31 to Ar-51 and Ar-53. Natural argon is a mixture of three stable isotopes: Ar-36 (0.34%), Ar-38 (0.06%), Ar-40 (99.6%). Ar-39 (half-life 269 yrs) is to determine the age of ice cores, ground water and igneous rocks. Appearance Under ordinary conditions, argon is a colorless, odorless, and flavorless gas. The liquid and solid forms are transparent, resembling water or nitrogen. In an electric field, ionized argon produces a characteristic lilac to violet glow. Properties Argon has a freezing point of -189.2Â °C, boiling point of -185.7Â °C, and density of 1.7837 g/l. Argon is considered to be a noble or inert gas and does not form true chemical compounds, although it does form a hydrate with a dissociation pressure of 105 atm at 0Â °C. Ion molecules of argon have been observed, including (ArKr), (ArXe), and (NeAr). Argon forms a clathrate with b hydroquinone, which is stable yet without true chemical bonds. Argon is two and a half times more soluble in water than nitrogen, with approximately the same solubility as oxygen. Argons emission spectrum includes a characteristic set of red lines. Uses Argon is used in electric lights and in fluorescent tubes, photo tubes, glow tubes, and in lasers. Argon is used as an inert gas for welding and cutting, blanketing reactive elements, and as a protective (nonreactive) atmosphere for growing crystals of silicon and germanium. Sources Argon gas is prepared by fractionating liquid air. The Earths atmosphere contains 0.94% argon. Mars atmosphere contains 1.6% Argon-40 and 5 ppm Argon-36. Toxicity Because it is inert, argon is considered to be non-toxic. It is a normal component of air that we breathe every day. Argon is used in blue argon laser to repair eye defects and kill tumors. Argon gas may replace nitrogen in underwater breathing mixtures (Argox) to help reduce the incidence of decompression sickness. Although argon is non-toxic, it is considerably more dense than air. In an enclosed space, it may present an asphyxiation risk, particularly near ground level. Element Classification Inert Gas Density (g/cc) 1.40 ( -186 Â °C) Melting Point (K) 83.8 Boiling Point (K) 87.3 Appearance Colorless, tasteless, odorless noble gas Atomic Radius (pm):Â  2- Atomic Volume (cc/mol): 24.2 Covalent Radius (pm): 98 Specific Heat (20Â °C J/g mol): 0.138 Evaporation Heat (kJ/mol): 6.52 Debye Temperature (K): 85.00 Pauling Negativity Number: 0.0 First Ionizing Energy (kJ/mol): 1519.6 Lattice Structure: Face-Centered Cubic Lattice Constant (Ã…): 5.260 CAS Registry Number: 7440–37–1 Argon Trivia The first noble gas to be discovered was argon.Argon glows violet in a gas discharge tube. It is the gas found in plasma balls.William Ramsay, in addition to argon, discovered all the noble gases except radon. This earned him the 1904 Noble Prize in Chemistry.The original atomic symbol for argon was A. In 1957, the IUPAC changed the symbol to the current Ar.Argon is the 3rd most common gas in Earths atmosphere.Argon is produced commercially by fractional distillation of air.Substances are stored in argon gas to prevent interactions with the atmosphere. Sources Brown, T. L.; Bursten, B. E.; LeMay, H. E. (2006). J. Challice; N. Folchetti, eds. Chemistry: The Central Science (10th ed.). Pearson Education. pp. 276 289. ISBN 978-0-13-109686-8.Haynes, William M., ed. (2011). CRC Handbook of Chemistry and Physics (92nd ed.). Boca Raton, FL: CRC Press. p. 4.121. ISBN 1439855110.Shuen-Chen Hwang, Robert D. Lein, Daniel A. Morgan (2005). Noble Gases. Kirk Othmer Encyclopedia of Chemical Technology. Wiley. pp. 343–383.Weast, Robert (1984). CRC, Handbook of Chemistry and Physics. Boca Raton, Florida: Chemical Rubber Company Publishing. pp. E110. ISBN 0-8493-0464-4.

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HR Strategic Planning MODULE 1 Discussion - Essay Example This explains why team work is emphasized in a business organization as its various units need to collaborate together for it to function. For example, the goal of marketing is integrated into manufacturing for the factory people realize the need of customer satisfaction. Information and knowledge are also shared through the various channels in the organization to promote cohesion, knowledge and skills across organization (Kahn and Mentzer, 1998). Departments may not be well verse in other functions of the business but they are aware that their output are needed by other departments and that they are also dependent on the output of others. One of the concrete example where the various department and functions intersect with each other is through a project which is increasingly becoming common in business organizations. Projects are typically composed of people in the organization from various departments with different background and skillsets working together in order to achieve the goal of the

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Wall Street Journal Executive Summary - Essay Example This lending has brought a new life to Ms. Mathews’ family business and also to her bank. â€Å"For a lot of the big regional banks, the future is a return to the past, â€Å"says Eric Wasserstrom, an analyst at Guggenheim Securities LLC. ’’It’s more like their traditional lending, more balanced† (Sterngold Web). After the recession, some businessmen and lawmakers, said banks were not playing their part in economic growth, although they received a lot of funds from the government. Banks increased their lending across the country in the second quarter of 2012.since then they have increased their lending. However, not all banks accelerated their lending. Some local banks increased their lending to businesses earlier than the national banks in past recession period. The volume of commercial and industrial loans at the major street banks is larger in dollar terms than at regional lenders, although the loans only make a small amount of their total share. For example, Bank of American Corp. made $233.6 billion in loans in 2014 which was 26.5 percent of its total and Citigroup Inc. 6.4 percent of its total. Large banks are mostly concentrating on giving the other types of loans; smaller banks put much emphasis on loaning business persons. KeyBank, for instance, increased its commercial and industrial loan by 12.3 percent in 2014, taking a lion share among its peers in 2014. Fifth Third Bancorp increased its bank loan by 4 percent last year and PNC Financial Services grew hers by 10 percent. KeyBank is established in 12 states, from Maine to Alaska. In July it announced that it had agreed to own Pacific Crest Securities, a technology focussed investment bank. The stock price for KeyCorp, the holding company which consists almost entirely of the banking operation has out competed most of its competitors. During the recession of 2008 and 2009, KeyBank just like the other banks was affected by the economic crisis. It

Collective Bargaining Essay -- Labor Unions

Collective Bargaining Unions provide a vital service for employees and management by negotiating contracts, ensuring workplace safety, and representing employees in grievance hearings. While there are hundreds of unions in the United States, this paper focuses on three major unions, the National Treasury Employees Union (NTEU), the American Federation of State, County, and Municipal Employees (AFSCME), and the American Federation of Teachers (AFT). Furthermore, this paper will compare and contrast these agencies, summarize their roles in optimizing employee relations with organizations, describe four challenges management and union officials face, and evaluate privatization as a means of breaking public employee unions. Compare and Contrast Three Unions The NTEU started in 1938 as the National Association of Employees of Collectors of the Internal Revenue (NAECIR) to reflect their expanded membership they changed their name to NTEU in 1973 (History of NTEU, n.d.). The NTEU is an independent organization whose mission is "to organize federal employees to work together to ensure that every federal employee is treated with dignity" (Who We Are, n.d.). While the AFSCME started in 1932, in response to the depression and out fear of the reestablishment of the spoils system their mission "to promote, defend, and enhance the civil service system" (AFSCME: 75 Years of History, n.d.). Whereas the AFT started in 1916 Chicago as part of their mission, they sought to increase wages for all members including women and minorities (AFT History, n.d.). Consequently, the AFT and the AFSCME full under the AFL-CIO and the NTEU remains independent. While the AFT focuses on educators, the AFSCME centers on state and local employees and... ...s, R. S. (2011). Blue-collar public servants : How union membership influences public service motivation. The American Review of Public Administration, 41(6), 705-723. doi:10.1177/0275074010392367 Kearney, R. C. (2011). Randi Weingarten, the American Federation of Teachers, and the challenges of policy leadership in a hostile environment. Public Administration Review, 71(5), 772-781. doi:10.1111/j.1540-6210.2011.02418.x Masters, M. F. (1998). AFSCME as a political union. Journal of Labor Research, 19(2), 313-350. Perry, J. L., & Wise, L. R. (1990). The motivational bases of public service. Public Administration Review, 50(3), 367-373. Retrieved from http://www.jstor.org/stable/976618 Tobias, R. M. (2004). The future of federal government labor relations and the mutual interests of congress, the administration, and unions. Journal of Labor Research, 25(1), 19-41. Collective Bargaining Essay -- Labor Unions Collective Bargaining Unions provide a vital service for employees and management by negotiating contracts, ensuring workplace safety, and representing employees in grievance hearings. While there are hundreds of unions in the United States, this paper focuses on three major unions, the National Treasury Employees Union (NTEU), the American Federation of State, County, and Municipal Employees (AFSCME), and the American Federation of Teachers (AFT). Furthermore, this paper will compare and contrast these agencies, summarize their roles in optimizing employee relations with organizations, describe four challenges management and union officials face, and evaluate privatization as a means of breaking public employee unions. Compare and Contrast Three Unions The NTEU started in 1938 as the National Association of Employees of Collectors of the Internal Revenue (NAECIR) to reflect their expanded membership they changed their name to NTEU in 1973 (History of NTEU, n.d.). The NTEU is an independent organization whose mission is "to organize federal employees to work together to ensure that every federal employee is treated with dignity" (Who We Are, n.d.). While the AFSCME started in 1932, in response to the depression and out fear of the reestablishment of the spoils system their mission "to promote, defend, and enhance the civil service system" (AFSCME: 75 Years of History, n.d.). Whereas the AFT started in 1916 Chicago as part of their mission, they sought to increase wages for all members including women and minorities (AFT History, n.d.). Consequently, the AFT and the AFSCME full under the AFL-CIO and the NTEU remains independent. While the AFT focuses on educators, the AFSCME centers on state and local employees and... ...s, R. S. (2011). Blue-collar public servants : How union membership influences public service motivation. The American Review of Public Administration, 41(6), 705-723. doi:10.1177/0275074010392367 Kearney, R. C. (2011). Randi Weingarten, the American Federation of Teachers, and the challenges of policy leadership in a hostile environment. 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