Rivero L.Encyclopedia of database technologies and applications.2006

KirkSt.Amant

Texas Tech University, USA

INTRODUCTION

Globalization is increasingly integrating the economies and the societies of the world. Now, products created in one nation are often marketed to a wide range of international consumers. Similarly, the rapid diffusion of online media has led to an increase in cross-border interactions on both a social and a professional level. Differing cultural expectations, however, can result in miscommunications within this new paradigm of global discourse. Individuals working within this international framework therefore need to understand the process of localization in order to operate more effectively under such a global paradigm. This paper overviews localization, why it is important, and how it might affect professional activities in the future.

BACKGROUND

To understand localization, one must first understand how rhetoric, or the way in which information is presented, can vary along cultural lines. The idea works as follows: Each culture has its own set of rhetorical expectations, or conditions, for how to convey ideas effectively (Kaplan, 2001; Woolever, 2001). If one presents information in a way that meets the rhetorical expectations of a particular group, then group members will be more inclined to consider that information credible or usable (Bliss, 2001). If one presents information in a way that fails to address a group’s rhetorical expectations or that conflicts with those expectations, then the group will view that information as noncredible and will be less inclined to use it. Moreover, if noncredible messages are associated with a particular product, audiences might consider that item as not worth purchasing or using (Ulijn & Strother, 1995).

Just as cultures have different rhetorical expectations, information considered credible and effective by one cultural group might be deemed suspect or unusable by another (Kaplan, 2001; Ulijn & St.Amant, 2000; Woolever, 2001). Language is perhaps the most obvious factor related to credibility in cross-cultural exchanges. If one wishes to develop informative materials for another culture, then concepts must be presented in the language

used by that group. That is, if one wishes to target information for an audience in France, one should use the French language when presenting ideas.

Using the correct language, however, is often not enough, for cultural groups can have different norms for how ideas should be expressed within a language (Bliss, 2001; Driskill, 1996; Kaplan, 2001; Ulijn, 1996). These expectations, moreover, often reflect deep-seated cultural values or societal rules (Ferraro, 2002; Neuliep, 2000). As a result, it can often be difficult for the members of one culture to anticipate the rhetorical expectations another cultural group associates with a credible presentation.

Some cultures, for example, tend to prefer more linear/ focused presentations in which facts, connections between ideas, and conclusions are explicitly stated (Campbell, 1998; Ulijn & St.Amant, 2000). Other cultures, however, might prefer more indirect and seemingly circular presentations in which individuals seem to go off on tangents, insert seemingly “random” historical examples, or avoid directly stating facts or conclusions (Campbell, 1998; Ulijn & St.Amant, 2000; Woolever, 2001). These variations can lead to misperceptions or confusion when different cultural groups interact. Ulijn and St.Amant (2000), for example, note that many Western cultures prefer a more direct presentation of information, while many Eastern cultures use a more indirect approach when sharing ideas. As a result, the indirect style used by Eastern cultures is often viewed as “shifty” by Westerners who expect presenters to “get to the point.” (In such cultures, a lack of directness equals “dishonesty.”) Conversely, many Easterners tend to view the direct presentation style of Western cultures as “rude,” for by directly stating information, an individual is patronizing or talking down to the audience. In such cases, by failing to address the rhetorical expectations of the “other” culture, individuals unknowingly undermine their own credibility in cross-cultural exchanges.

Another interesting factor is that cultural rhetorical expectations are not restricted to verbal presentations. Rather, they also affect how different groups perceive and respond to visual displays. As a result, the physical appearance of an object, can differ from country to country. For example, the cultural expectations of what features an item—or visual representations of an item—should

possess can differ from country to country. Such differences can affect how audiences perceive the credibility and the acceptability of visual displays (Kamath, 2000; Lustig & Koester, 1999; Neuliep, 2000).

For example, the perception of a mailbox being a metal or wooden box that sits atop of a post and that has a red flag on the side of it is, essentially, an American one (Gillette, 1999). In other cultures, a mailbox might be a small door in a wall or even a cylindrical metal container that resembles an American fire hydrant. These design discrepancies could then cause confusion when using images to share information across cultures. Consider the following situation: International users come to a Web portal and expect to find a “mail” function. To address this expectation, the portal’s creators have included an “access mail” icon into the portal’s design. The image used for this icon, however, is an American-style mailbox. Unfortunately, this choice of image renders that depiction unrecognizable to users from different cultures—cultures in which mailboxes have very different characteristics. Those individuals might then consider the associated Web portal noncredible, for they perceive it as lacking a key design feature expected of credible Web portals. In this way, cultural differences in visual expectations can affect entire sites that use a particular kind of image.

Moreover, the presence or absence of a single design aspect or feature can be enough to affect the credibility of an image or of an overall Web site. In some cases, cultures can associate different meanings with the same color (Conway & Morrison, 1999; Ferraro, 2002). These associations could thus affect how individuals from different cultures perceive the meaning of a particular image. In the United States, for example, a blue ribbon usually indicates a winner (first place), whereas the same color ribbon in the United Kingdom often indicates second place (in the United Kingdom, a red ribbon is used to signify “first place/winner”). The different associations related to the color blue could affect how Americans vs. Brits perceive a “blue ribbon product” (first rate vs. second rate). In terms of Web design, one might consider how the blue ribbon image associate with the Electronic Frontier Foundation’s (EFF) Blue Ribbon Campaign for Free Speech Online—an icon proudly displayed by many U.S. Web sites—could affect U.K. users’ perceptions of the quality of information found on such sites (second-rate information).

The various expectations cultures can have for visual and verbal communication can markedly affect the success of cross-cultural exchanges. For these reasons, individuals can greatly benefit from practices that address cultural rhetorical differences on both a verbal and a visual level. Localization is a process dedicated to addressing such differences by revising or developing materials in a way that meets the communication expectations of different cultures.

MAIN THRUST OF THIS ARTICLE

4

Localization is a process in which professionals design or revise materials to meet the rhetorical expectations of a particular cultural group (Esselink, 2000; Yunker, 2003). Often abbreviated as L10N (for the 10 letters between the “L” and the “N” in “localization”), localization generally involves one of two processes. In both cases, a company or organization wishes to share information with different cultural audiences. The time at which such international sharing takes place, however, affects the tasks of the localizer and the overall process.

In the first scenario, the localization process begins with the creation of original source materials, which are items designed for audiences from a particular cultural group (Esselink, 2000; Yunker, 2003). In such cases, an organization initially creates a product for a particular cultural audience. Both the product and its related documentation are then designed to meet the rhetorical expectations that culture associates with credibility. Over time, the company decides to market the product in other nations. The design of the original item and its related materials might, however, conflict with the rhetorical expectations of those “other” cultural audiences. It is at this point that localizers are used to redesign the product to make it appear credible to users from those other cultures (Esselink, 2000; Yunker, 2003). The task of the localizer then becomes a matter of converting information from the rhetorical styles used in source (original) materials to those of a different cultural audience (often known as the target audience).

In performing such “after-the-fact” conversions, localizers often deal with factors of translation (language) and visual design, in terms of both layout and image use. In such cases, the text is often translated into the language of the desired target audience, and visual and design factors are either revised or replaced in order to match the expectations that same audience (Esselink, 2000; Yunker, 2003). Ideally, this process is a relatively simple “find-and-replace” activity in which items in source materials are replaced with culture specific items for other audiences. Unfortunately, certain factors can affect the ease with which localizers can accomplish such a process.

One of the more interesting problems is text expansion. The idea is that information that can be conveyed with a single word in one language might require multiple words to convey the same meaning in another tongue (Esselink, 2000; Yunker, 2003). The English-language expression “overtime pay” (two words), for example, is often translated as “remuneration des herues supplementaires” (four words) in French. Even in cases in which a single word is used to convey the same concept in different languages, the length of the related word could vary considerably. The English word help

(four letters), for example, can be translated into assistance (10 letters) in French.

This factor of text expansion is important, for it can affect the design of an overall item. Software products, for example, might use drop-down menus to provide access to different program features. These menus, however, are often configured so that their width accommodates the longest line of text in the original source language. The formatting of a drop-down menu might therefore require redesign to accommodate the text expansion needed to insert corresponding information presented in another language. Moreover, changes resulting from text expansion could require individuals to reconfigure an overall interface to accommodate all of the textual features associated with a program (Esselink, 2000; Yunker, 2003). Similarly, Web site features such as menu buttons or menu options might require redesign to accommodate text expansion. In such cases, the overall size and structure of menu bars or Web pages might also need to be reconfigured to accommodate such changes.

In other instances, the localizer might have to remove or replace certain design features, such as pictures or icons, to address the visual sensibilities of different target cultures (Esselink, 2000; Yunker, 2003). The removal or replacement of such items, however, might create gaps in the overall interface or change the layout of an interface depending on the size of the images that are removed or replaced. As a result, the overall layout of the item might need to be redesigned to accommodate such changes. Additionally, the expectations of a target culture might be so different that creating a localized item involves an entire redesign of an overall product. These factors are only made more complex as after-the-fact localization is often done on relatively tight schedules and with limited budgets. In such cases, localizers often find themselves balancing issues of quality with those of cost and time.

In a second and a more ideal situation, localization would take place from the very beginning of a product’s development (Esselink, 2000; Yunker, 2003). In these cases, localizers would do more than simply “revise” source texts created for one specific culture. Rather, localizers would simultaneously generate original source materials for different cultural audiences. Such a process would allow for the simultaneous release of a product into different overseas markets. While such processes seem both time and cost intensive, the quality of the resulting materials would generally be better than items localized after the fact and on a tighter time frame.

Another benefit of simultaneous localization is that localizers might notice design factors, such as the construction of an interface, that would render a particular product less usable (if not unusable) by a certain cultural audience (Esselink, 2000; Yunker, 2003). The localizer

could then present this problem to the designer creating the product. Such consultations allow developers to revise a product during vs. after the initial design process and alleviate many of the problems related to reengineering completed products.

In both scenarios (i.e., after the fact and during development), localization facilitates the flow of information from one cultural group to another by revising materials to meet different rhetorical expectations. While localization practices often focus on products or product related services, localization can be adapted to address processes. Perhaps the most influential reason for such an adaptation is the spread of a production approach known as international outsourcing.

FUTURE TRENDS

In the past five years, global Internet access has grown dramatically—especially in developing nations. China, for example, has seen its Internet use grow from 2.1 million persons in 1999 to nearly 60 million by the end of 2002 (Section IV Survey Results, 2003; Wired China, 2000). In Africa, the United Nations and private companies have undertaken initiatives to increase online access in specific nations and to the continent in general (Kalia, 2001; Tapping in to Africa, 2000). In Latin America, Global Crossings Ltd. has completed a project that uses fiber optics to give, “multinational companies the ability to communicate with Latin America as efficiently as with any other region” (Tying Latin America Together, 2001, p. 9). And in Eastern Europe, the number of individuals going online is expected to climb from 17% to 27% by 2006 (IDC Research, 2003).

This increased global access has prompted many companies to explore different production methods involving online communication technologies. Perhaps one of the most interesting of these approaches is international outsourcing, a process in which organizations use online media to exchange information and electronic products (e.g., software) with employees located in other countries. The benefit of this process is easy access to labor forces in other countries—namely developing nations with skilled technical workers who can provide services for a fraction of what they would cost in industrialized countries. Online media allow these international workers to exchange information directly and quickly with one another and with the company sponsoring a project. This speed and directness also mean that

•Different parts of an overall process can be performed simultaneously in different locations, and

•Electronic products (e.g., software) can be forwarded from one location/time zone to another in a manner that would allow work to continue without pause.

Ideally, such processes result in a quality item that can be completed more quickly and at a fraction of the cost it would have taken to produce domestically. These benefits have inspired both private companies and municipal governments to use international outsourcing for everything from computer programming and information technology (IT) work to accounting practices and the staffing of call centers (The New Geography, 2003; Relocating the Back Office, 2003). Moreover, trends in IT and in demographics indicate that offshoring practices will increase in coming years. (For a more detailed discussion of this topic, see Drucker, 2001; Lui & Chan, 2003.)

The key to success in these situations is effective communication. For example, any ignored or misinterpreted information could result in overseas employees performing a process incorrectly. Moreover, the speed with which such processes take place, when combined with the physical and cultural distance separating participants, means that mistakes might go unnoticed until it is too late. Information therefore needs to be conveyed in a way that encourages participants to make use of it. Localization thus becomes an important process, for it increases the chances that outsourcing workers will use essential materials.

Within international outsourcing, localization can take place at two levels. The first level is interface design, and it involves the medium through which individuals interact. In many cases, participants involved in outsourcing come to a central online location (e.g., a company portal or Web page) to collect, present, or exchange information related to a particular product or production process. These interfaces, however, must be designed to encourage use if all involved parties perform their tasks correctly. In these cases, localizers can facilitate the exchange of information by designing interfaces in a way that meets the credibility expectations of different cultures and thus encourages use and information exchange.

The second level of localization application involves how individuals communicate via online media, such as e- mail, chat rooms, and bulletin boards. In these scenarios, participants need to know two important pieces of rhetorical information:

1.How to draft online messages that recipients from other cultural groups will consider credible and worth responding to.

2.How to interpret verbal messages constructed according to different cultural rhetorical norms.

In both cases, localizers can provide participants with

two communication “cheat sheets” that address these 4 factors. The first kind of cheat sheet would explain how to

draft messages that address the rhetorical expectations of other cultural groups involved in the outsourcing process. The second kind of cheat sheet would tell users how to interpret the meaning that individuals from other cultures convey via a particular rhetorical structure. By teaching others how to address rhetorical factors within the communication process, localizers enhance the chances that participants in international outsourcing activities correctly present and interpret information. Such approaches contribute to the success of projects involving outsourcing.

CONCLUSION

The global nature of modern business means that individuals must now consider interactions in terms of international audiences. These audiences, however, can have different expectations of how information should be presented in an exchange. Fortunately, localization can facilitate cross-cultural interactions by converting materials from one cultural rhetorical style to another. While localization has historically dealt with products, the shift to international outsourcing allows localization to address processes as well. Thus, by understanding what localization is and how it works, organizations can increase their successes in a variety of cross-cultural communication situations.

REFERENCES

Bliss, A. (2001). Rhetorical structures for multilingual and multicultural students. In C. G. Panetta (Ed.), Contrastive rhetoric revisited and redefined (pp. 15-30). Mahwah, NJ: Erlbaum.

Campbell, C. P. (1998). Rhetorical ethos: A bridge between high-context and low-context cultures? In S. Niemeier, C. P. Campbell, & R. Dirven (Eds.), The cultural context in business communication (pp. 3147). Philadelphia: John Benjamin.

Conway, W. A., & Morrison, T. (1999). The color of money. Global Business Basics. Retrieved December 10, 1999, from http://www.getcustom.com/omnibus/ iw0897.html

Driskill, L. (1996). Collaborating across national and cultural borders. In D. C. Andrews (Ed.), International dimensions of technical communication (pp. 21-44). Arlington, VA: Society for Technical Communication.

Drucker, P. (2001, November 1). The next society: A survey of the near future. The Economist, pp. 3-5.

Esselink, B. (2000). A practical guide to localization.

Philadelphia: John Benjamin.

Ferraro, G. (2002). Global brains: Knowledge and competencies for the 21st century. Charlotte, NC: Intercultural Associates.

Gillette, D. (1999, December). Web design for international audiences. Intercom, p. 15-17.

IDC research: Net usage up in Central and Eastern Europe. (2003, Feb. 19). NUA Internet surveys. Retrieved June 23, 2003, from http://www.nua.com/surveys/ index.cgi?f=VS&art_id=905358723&rel=true

Kalia, K. (2001, July/August). Bridging global digital divides. Silicon Valley Reporter, pp. 52-54.

Kamath, G. R. (2000, May). The India paradox. Intercom, pp. 10-11.

Kaplan, R. B. (2001). Foreword: What in the world is contrastive rhetoric? In C. G. Panetta (Ed.), Contrastive rhetoric revisited and redefined (pp. vii-xx). Mahwah, NJ: Erlbaum.

Lui, K. M., & Chan, K. C. C. (2003). Inexperienced software team and global software team. In A. Gunasekaran, O. Khalil, & S. M. Rahman (Eds.), Knowledge and information technology management: Human and social perspectives (pp. 305-323). Hershey, PA: Idea Group.

Lustig, M., & Koester, J. (1999). Intercultural competence: Interpersonal communication across cultures

(3rd ed.). New York: Longman.

Neuliep, J. W. (2000). Intercultural communication: A contextual approach. Boston: Houghton Mifflin.

The new geography of the IT industry. (2003, July 17). The Economist. Retrieved December 20, 2003, from http:/ / w w w . e c o n o m i s t . c o m / d i s p l a y s t o r y . c f m ? s t o r y _ i d = S % 2 7 % 2 9 H H % 2 E Q A % 5 B % 2 1 % 23%40%21D%0A

Relocating the back office. (2003, December 11). The Economist. Retrieved December 20, 2003, from http:/ / w w w . e c o n o m i s t . c o m / d i s p l a y s t o r y . c f m ? story_id=2282381

Section IV survey results. (2003, January). Semiannual report on the development of China’s Internet. Retrieved June 25, 2003, from http://www.cnnic.net.cn/develst/ 2003-1e/444.shtml

Tapping in to Africa. (2000, September 9-15). The Economist, p. 49.

Tying Latin America together. (2001, Summer). NYSE Magazine, p. 9.

Ulijn, J. M. (1996). Translating the culture of technical documents: Some experimental evidence. In D. C. Andrews (Ed.), International dimensions of technical communication (pp. 69-86). Arlington, VA: Society for Technical Communication.

Ulijn, J. M., & St.Amant, K. (2000). Mutual intercultural perception: How does it affect technical communication– Some data from China, the Netherlands, Germany, France, and Italy. Technical Communication, 47 (2), 220-237.

Ulijn, J. M., & Strother, J. B. (1995). Communicating in business and technology: From psycholinguistic theory to international practice. Frankfurt, Germany: Peter Lang.

Wired China. (2000, July 22). The Economist, pp. 24-28.

Woolever, K. R. (2001). Doing global business in the information age: Rhetorical contrasts in the business and technical professions. In C. G. Paneta (Ed.), Contrastive rhetoric revisited and redefined (pp. 47-64). Mahwah, NJ: Erlbaum.

Yunker, J. (2003). Beyond borders: Web globalization strategies. Boston: New Riders.

KEY TERMS

International Outsourcing: Production process in which individuals in other nations perform work for an organization.

Localization: The process of revising materials designed for one particular culture to meet the communication expectations of a different cultural group.

Online Media: Electronic communication technologies that rely on the Internet or the World Wide Web as a mechanism for presenting or exchanging information.

Rhetoric: The manner in which information is presented.

Source–Source Text–Source Materials: Original materials designed for a specific cultural group.

Target Culture: The culture for which one revises source materials in the localization process.

Text Expansion: Situation in which one language requires more words to express the same meaning than does another language.

INTRODUCTION

Rough set theory is a new mathematical approach to imperfect knowledge. The problem of imperfect knowledge, tackled for a long time by philosophers, logicians, and mathematicians, has become also a crucial issue for computer scientists, particularly in the area of artificial intelligence. There are many approaches to the problem of how to understand and manipulate imperfect knowledge. The most successful one is, no doubt, fuzzy set theory proposed by Zadeh (1965). Rough set theory (Pawlak, 1982) presents still another attempt at this problem. This theory has attracted the attention of many researchers and practitioners all over the world, who contributed essentially to its development and applications. The rough set approach seems to be of fundamental importance to AI and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, inductive reasoning, and pattern recognition.

The rough set approach provides efficient algorithms for finding hidden patterns in data, minimal sets of data (data reduction), evaluating the significance of data, and generating sets of decision rules from data. This approach is easy to understand and offers straightforward interpretation of obtained results, and most of its algorithms are particularly suited for parallel processing.

The rough set philosophy is founded on the assumption that with every object of the universe of discourse we associate some information. For example, if objects are patients suffering from a certain disease, symptoms of the disease form information about patients. Objects characterized by the same information are indiscernible (similar) in view of the available information about them. The indiscernibility relation generated in this way is the mathematical basis of rough set theory.

Any set of all indiscernible (similar) objects is called an elementary set (neighborhood) and forms a basic granule (atom) of knowledge about the universe. Any

union of elementary sets is referred to as a crisp (precise) set; otherwise, the set is rough (imprecise, vague).

Consequently each rough set has boundary-line cases, i.e., objects which cannot with certainty be classified either as members of the set or of its complement. Obviously crisp sets have no boundary-line elements at all. This means that boundary-line cases cannot be properly classified by employing the available knowledge.

Vague concepts, in contrast to precise concepts, cannot be characterized in terms of information about their elements. Therefore, in the proposed approach, we assume that any vague concept is replaced by a pair of precise concepts, called the lower and the upper approximation of the vague concept. The lower approximation consists of all objects which surely belong to the concept, and the upper approximation contains all objects which possibly belong to the concept. The difference between the upper and the lower approximation constitutes the boundary region of the vague concept. Approximations are two basic operations in rough set theory. The observation that vague concepts should have a nonempty boundary was made by Gottlob Frege in the beginning of 20th century.

BACKGROUND

In Table 1, we consider essential issues in rough sets in more detail.

ROUGH SETS AS A TOOL FOR REASONING ABOUT VAGUE CONCEPTS

Vague complex concept approximation and reasoning about vague concepts by means of such approximations become critical for numerous applications related to multiagent systems (such as Web mining, e-commerce,

monitoring, security and rescue tasks in multiagent systems, cooperative problem solving, intelligent smart sensor fusion, human-computer interfaces, telemedicine, and soft views of databases for specific customers). Further development of such methods for approximate reasoning by intelligent agents (Russell & Norvig, 2003) based on databases and knowledge bases is needed.

Tasks collected under the labels of data mining, knowledge discovery, decision support, pattern classification, and approximate reasoning require tools aimed at discovering templates (patterns) in data and classifying them into certain decision classes. Templates are in many cases the most frequent sequences of events, most probable events, regular configurations of objects, the decision rules of high quality, and approximate reasoning schemes. Tools for discovering and classifying templates are based on reasoning schemes rooted in various paradigms (Kloesgen & Zytkow, 2002). Such patterns can be extracted from data by means of methods based on Boolean reasoning and discernibility. The discernibility relation (in the simplest case defined as the complement of the indicernibility relation) is one of the most important relations considered in rough set theory. The ability to discern between per-

ceived objects is important for constructing many entities like reducts, decision rules, or decision algorithms. The idea of Boolean reasoning is based on construction for a given problem P of a corresponding Boolean function fP with the following property: The solutions for the problem P can be decoded from prime implicants of the Boolean function fP. Let us mention that to solve real-life problems it is necessary to deal with Boolean functions having a large number of variables.

A list of some current research directions on the rough set foundations and the rough-set-based methods is presented in Table 2.

For more details the reader is referred to the enclosed bibliography on rough sets (Demri & Or;owska, 2002; Lin & Cercone, 1997; Pal et al., 2004; Pal & Skowron, 1999; Pawlak, 1991; Polkowski, 2002; Polkowski & Skowron, 1998; Polkowski et al., 2000 ).

FUTURE PLANS

To enhance the above-mentioned methods (see Table 3), further development of methods based on rough sets in

combination with other soft computing techniques is needed. In particular, methods based on rough mereological approach (Polkowski & Skowron, 1996) combined with information granulation (Pal et al., 2004) seems to be very promising. Among issues to be investigated are scalability problems, methods for designing adaptive systems, and methods for constructing intelligent sys-

tems that perform computations with words and perceptions (Zadeh, 2001).

CONCLUSION

Rough set theory supplies essential tools for knowledge analysis. It allows for creating algorithms for knowledge

Rough Sets

reduction, concept approximation, decision rule induction, and object classification. The methods of rough set theory rest on indiscernibility and related notions, in particular, on notions related to rough inclusions. All constructs needed in implementing rough-set-based algorithms can be derived from data tables with need for neither a priori estimates nor preliminary assumptions. Currently, research in rough set theory is directed, among others, at problems of knowledge granulation, techniques for computing with words and perceptions, and roughneural computing (Pal et al., 2004).

REFERENCES

Bazan, J., Nguyen, H. S., Nguyen, S. H., Synak, P., & Wróblewski, J. (2000). Rough set algorithms in classification problems. In L. Polkowski, S. Tsumoto, & T. Y. Lin (Eds.), Rough set methods and applications: New developments in knowledge discovery in information systems

(pp. 49-88). Heidelberg, Germany: Physica-Verlag.

Demri, S., & Orlowska, E. (2002). Incomplete information: Structure, inference, complexity. Heidelberg, Germany: Springer-Verlag.

Kloesgen, W., & Zytkow, J. (Eds.). (2002). Handbook of knowledge discovery and data mining. Oxford, UK: Oxford University Press.

Lin, T. Y., & Cercone, N. (1997). Rough sets and data mining: Analysis of imperfect data. Boston: Kluwer Academic.

Lukasiewicz, J. (1970). Die logischen Grundlagen der Wahrscheinlichkeitsrechnung (1913). In L. Borkowski (Ed.), Jan Lukasiewicz: Selected works, Amsterdam; Warsaw, Poland: Polish Scientific Publishers and NorthHolland

Pal, S. K., Polkowski, L., & Skowron, A. (Eds.). (2004).

Rough-neural computing: Techniques for computing with words. Berlin, Germany: Springer-Verlag.

Pal, S. K., & Skowron, A. (1999). Rough fuzzy hybridization: A new trend in decision-making. Singapore: Springer-Verlag.

Pawlak, Z. (1982). Rough sets, International Journal of Computer and Information Sciences, 11, 341-356.

Pawlak, Z. (1991). Rough sets: Theoretical aspects of reasoning about data. Dordrecht, Germany: Kluwer.

Pawlak, Z., & Skowron, A. (1994). Rough membership functions.InR. R. Yager, M. Fedrizzi, & J. Kacprzyk (Eds.),

Polkowski, L. (2002). Rough sets: Mathematical foundations. Heidelberg, Germany: Physica-Verlag.

Polkowski, L., Tsumoto, S., & Lin, T. Y. (Eds.). (2000).

Rough set methods and applications: New developments in knowledge discovery in information systems. Heidelberg, Germany: Physica-Verlag.

Polkowski, L., & Skowron, A. (1996). Rough mereology: A new paradigm for approximate reasoning., International Journal of Approximate Reasoning, 15(4), 333365.

Polkowski, L., & Skowron, A. (Eds.). (1998). Rough sets in knowledge discovery 1 & 2. Heidelberg, Germany: Physica-Verlag.

Russell, S .J., & Norvig, P. (2003). Artificial intelligence. A modern approach. Saddle River, NJ: Prentice Hall.

Skowron, A., & Rauszer, C. (1992). The discernibility matrices and functions in information systems. In R. Slowiñski (Ed.), Intelligent decision support: Handbook of applications and advances of the rough sets theory

(pp. 331-362). Dordrecht, Germany: Kluwer.

Skowron, A., & Stepaniuk, J. (2001). Information granules: Towards foundations of granular computing. International Journal of Intelligent Systems, 16(1), 57-86.

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.

Zadeh, L. A. (2001). A new direction in AI: Toward a computational theory of perceptions. AI Magazine, 22(1), 73-84.

KEY TERMS

Boolean Reasoning: Is based on construction for a given problem P of a corresponding Boolean function fP with the following property: The solutions for the problem P can be decoded from prime implicants of the Boolean function fP.

Decision Rule: In (U,A,d) is any expression of the form {a=va : a A and va Va}→d=v where d is the decision attribute and v is a decision value. This decision rule is true in (U,A,d) if for any object satisfying its lefthand side it also satisfies the right-hand side; otherwise, the decision rule is true to a degree measured by some coefficients such as confidence.