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Long Paper ACEEE Int. J. on Information Technology , Vol. 3, No. 3, Sept 2013 TABLE I. SAMPLE VALUES OF VARIABLES DESCRIBING CAPITAL B ARRIERS TO ENTRY.

T RE F – T EM PORAL RE FERENCE Past: Over previou s 3 months Som e ti me ago Last w eek On the recent Monda y Yest erday A few days ago Pre sent: In t he c urrent mont h In t he present qua rter This ye ar Today Now Fut ure: In t he m onth to c ome In t he forthco ming el ections W ill ta ke pl ace on M onday Next week Soo n Over the next 3 days Tomorrow Conti nuity: Si nce/from the end of Ju ne Over/during/for/ w ithin t he next few days In t he past t hree w eeks By/un til/t ill t he e nd of March 2003 The foll owi ng 3 weeks

D ER – DO LLAR ’S EXC HANGE RATE Sudden increase of DER Rapid incre ase of DER Signi fi cant increas e of DER In si gnificant increase of D ER U nexpected increase of D ER Previ ou sly une xpe ct ed i ncrea se of DER

OP – O IL PRIC ES S udden i ncrease o f OP R api d i ncrease of OP S ignific ant i ncrease of OP Insigni fi cant incre as e of O P U nexpected increase of O P P reviousl y u nexpect ed increase of O P

Sudden dec rease of D ER Rapid decrease o f DER Signi fi cant dec rease of D ER In si gnificant de crease of DER U nexpected de crea se of DER Previ ou sly une xpe ct ed decrease of D ER

S udden decrease of OP R api d decre as e of OP S ignific ant d ecrease of OP Insigni fi cant decrease of OP U nexpected decreas e of OP P reviousl y u nexpect ed de crease of OP

Low DER H igh DER Stable DER U nstabl e DER

Low OP H igh OP S table O P U nstable OP

Sudden cha nges of DER Rapid changes of D ER Signi fi cant cha nges of DER In si gnificant changes of DER U nexpected changes of DER Previ ou sly une xpe ct ed chan ges of DER Frequ ent changes of DER Frequ ent fluctuat ions of DER

S udden chan ges of OP R api d changes of OP S ignific ant chan ges of OP Insigni fi cant changes of O P U nexpected changes of O P P reviousl y u nexpect ed changes of OP F requent changes of OP F requent fl uctuati on s of O P

Strengt heni ng of dollar Weakening of dollar

Time stamp: As of May 2002 In t he first quarter of 2 004 On May 3, 200 5 On Tuesda y In J une Time fragment s: At the begi nn ing of/ start o f July From th e e nd of 2004 In mid/t he mi ddl e of July Early/ lat e in Jul y Intervals/operators: From Jun e 16 to July 1 0 Be twee n March and Ma y In fi ve weeks Tw o week s after C hri stmas Three days later Fi ve mont hs before/back /earlier

or oil price variable. Each premise contains also a temporal reference defining a temporal context of a rule. Sample possible values of variables in rules’ premises are shown in table 1. Although oil prices and dollar exchange rate are both typical numeric variables, they are described in a qualitative way, such an approach does not exclude the possibility of a quantitative description. It should be also pointed out that for this example a number of possible rules is 50.6221, but in reality it may be infinite, because the number of temporal references in natural language

In what follows, we present temporal knowledge about two barriers to entry, namely dollar exchange rate and oil prices. Next we present sample temporal rules concerning these barriers, and their formalization with temporal CGs. The rules have been formalized in the Prolog+CG language [15]. Prolog is one of the programming languages typically used in the AI, and the Prolog+CG version is a conceptual, object oriented extension of classical Prolog. It allows for using conceptual graphs as a basic data structure. For rule construction, three premise schemata were used: 1. Single premise: concerning either dollar exchange rate or oil prices, 2. A premise with conjunction of dollar exchange rate variable and oil price variable, 3. A premise with disjunction: dollar exchange rate variable © 2013 ACEEE DOI: 01.IJIT.3.3. 5

1 The number of rules was calculated using the decision table theory, by multiplying the number of values of each attribute in a premise by other numbers of attributes’ values.

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Temporal Knowledge, Temporal Ontologies, and Temporal Reasoning for Managerial Tasks  
Temporal Knowledge, Temporal Ontologies, and Temporal Reasoning for Managerial Tasks  

The paper is devoted to a variety of solutions aiming at taking time into account in economic and managerial analyses. It presents an exampl...

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