Enriching Domain Concepts with Qualitative Attributes (A Text Mining based Approach)

Attributes, whether qualitative or non-qualitative are the formal description of any real-world entity and are crucial in modern knowledge representation models like ontology. Though ample evidence for the amount of research done for mining non-qualitative attributes (like part-of relation) extraction from text as well as the Web is available in the wealth of literature, on the other side limited research can be found relating to qualitative attribute (i.e., size, color, taste etc.,) mining. Herein this research article an analytical framework has been proposed to retrieve qualitative attribute values from unstructured domain text. The research objective covers two aspects of information retrieval (1) acquiring quality values from unstructured text and (2) then assigning attribute to them by comparing the Google derived meaning or context of attributes as well as quality value (adjectives). The goal has been accomplished by using a framework which integrates Vector Space Modelling (VSM) with a probabilistic Multinomial Naive Bayes (MNB) classifier. Performance Evaluation has been carried out on two data sets (1) HeiPLAS Development Data set (106 adjective-noun exemplary phrases) and (2) a text data set in Medicinal Plant Domain (MPD). System is found to perform better with probabilistic approach compared to the existing pattern-based framework in the state of art

A CLOUD TOPSIS MODEL FOR GREEN SUPPLIER SELECTION

Due to stringent governmental regulations and increasing consciousness of the customers, the present day manufacturing organizations are continuously striving to engage green suppliers in their supply chain management systems. Selection of the most efficient green supplier is now not only dependant on the conventional evaluation criteria but it also includes various other sustainable parameters. This selection process has already been identified as a typical multi-criteria group decision-making task involving subjective judgments of different participating experts. In this paper, a green supplier selection problem for an automobile industry is solved while integrating the Cloud model with the technique for order of preference by similarity to an ideal solution (TOPSIS). The adopted method is capable of dealing with both fuzziness and randomness present in the human cognition process while appraising performance of the alternative green suppliers with respect to various evaluation criteria. This model identifies green supplier S4 as the best choice. The derived ranking results using the adopted model closely match with those obtained from other variants of the TOPSIS method. The Cloud model can efficiently take into account both fuzziness and randomness in a qualitative attribute, and effectively reconstruct the qualitative attribute into the corresponding quantitative score for effective evaluation and appraisal of the considered green suppliers. Comparison of the derived ranking results with other MCDM techniques proves applicability, potentiality and solution accuracy of the Cloud TOPSIS model for the green supplier selection.

Term intensity in linguistic studies

The article deals with the term intensity in linguistic research. The universality of the term emphasizes the fact that it is used in many fields of science and technology, when they talk about the intensity of the process, colour, light, sound. It is fixed in many special dictionaries. The term intensity is actively used in the field of linguistics. The study of intensity is an important aspect of linguistic research. This indicates the relevance of considering this term in linguistics. A circle of terms is outlined, which denotes the concept of intensity in linguistics. The terms intensity, amplification, intensity, intensifier, category of intensity is considered. The peculiarities of studying the studied terms in works on linguistics are shown. Interest in the notion of intensity in linguistics has been observed since the early 60’s of the XX century. But the term began to be actively used since the late 70’s of XX century. Intensity is interpreted as a component of semantics, in particular phraseological units. The category of intensity is general, open, and anthropocentric. It does not belong to a particular functional style. Scientists emphasize the ambiguous interpretation of this term. Researchers determine intensity as a category that represents the quantitative indicator of a qualitative attribute. Intensifiers are explicit means of amplification. Scientists call a large number of intensifiers. The intensities implicitly contain, in their significance, this amplification. Researchers also use the term intensive. A further study of terminology, which outlines the specificity of the identification of intensity at all levels of the language system, is promising.

Fuzzification - Decision Making in Terms of Uncertainty

Summary The theory of fuzzy sets allows to analyze insufficiently precise, accurate, complete phenomena which can not be modeled by the theory of probability or interval mathematics. We define fuzzy sets as sets where the boundary of the set is unclear and depends on subjective estimation or individual preference. In addition to the standard interpretation scale, described above, a set of numbers to each qualitative attribute must be assigned. In addition to the standard interpretation scale a set of numbers to each qualitative attribute must be assigned. First of all, it is necessary to determine the procedure for determining fuzzy numbers describing the attributes. One of the imperfections of the fuzzy sets is subjectivism when defining the boundaries of fuzzy sets and functions of belonging, which can significantly influence the final decision. The decision maker’s subjectivity is also present in the determination of weighted coefficients. However, in case of giving weight, fixed values are necessary. Some decisions require multidisciplinary knowledge, so the decision-making process includes more group decision-makers, who independently give their grades.

Impact Assessment From Coal Mining Area in Southern Brazil

The mining activity is highly environmental impacting, being the excavation process and waste sterile rejects crowding the main pollution sources. The Santa Catarina Coal Basin has great importance, considering that contains 4.3 billions tons of coal (13% of the Brazilian reserve) and 6.400 hectares of degraded area. That way, the study objective was to characterize and identify the ambient impacts derivated from coal mining activities, at the Sideropolis city, SC. The base method used to evaluate was The Leopold matrix which adaptations were made according to a qualitative attribute weighting matrix to verify the significance of impacts. The interaction between two actions of the enterprise and 11 generated environmental impacts was analysed according to the attributes of frequency, extension, duration, direction and degree, both in the physical and anthropic environments. All impacts had a negative direction, where the most striking activity was the opening of the cava, which, when forming the acidic lagoon, changes the surface water quality, being described as of great importance. Therefore, recognizing the principal environment problems could help on strategies to accomplish the recovery requirements of degraded areas on this area.