Dear Researcher

please check these attachments and refer to it.it will be helpful to get your answer.

Regards

http://www.sciencedirect.com/science/article/pii/S0377042706002160

see these papers also.

http://www.sciencedirect.com/science/article/pii/S0377042708000162

http://www.hindawi.com/journals/cmmm/2014/581316/

I have applied fuzzy soft sets for decision making in an imprecise environment and

have found it to be an effective technique.

Following paper elaborates on this approach:

http://www.sciencedirect.com/science/article/pii/S0377042706002160

Your Queries:

Q) Can fuzzy soft set be used without the comparison table?

A comparison table used in Fuzzy soft sets is required for element/parameter wise comparison of objects. Here by parameter, I mean the attributes which describe the

objects under comparison. The row-sum and column sum of objects is further used for ranking of the objects compared.  In most  of the decision making problems, after construction of comparison table the next step is computation of score followed by decision. So a comparison table is very much essential in decision making problems.  

Q) But what happens when am only concern about the truthfulness of a particular object in the domain, must I also have to make comparison with other objects in that domain?

By Truthfulness of a particular object in the domain do you mean you are only concerned with full/partial membership in the fuzzy sets? This can be achieved 

with regular fuzzy sets as well.

Q) Also how best can I handle the binary relationships that exist between the object of concern and other objects in the domain?

This can be done with a comparison table. 

I have applied fuzzy soft sets for decision making in an imprecise environment and

have found it to be an effective technique.

Following paper elaborates on this approach:

http://www.sciencedirect.com/science/article/pii/S0377042706002160

Your Queries:

Q) Can fuzzy soft set be used without the comparison table?

A comparison table used in Fuzzy soft sets is required for element/parameter wise comparison of objects. Here by parameter, I mean the attributes which describe the

objects under comparison. The row-sum and column sum of objects is further used for ranking of the objects compared.  In most  of the decision making problems, after construction of comparison table the next step is computation of score followed by decision. So a comparison table is very much essential in decision making problems.  

Q) But what happens when am only concern about the truthfulness of a particular object in the domain, must I also have to make comparison with other objects in that domain?

By Truthfulness of a particular object in the domain do you mean you are only concerned with full/partial membership in the fuzzy sets? This can be achieved 

with regular fuzzy sets as well.

Q) Also how best can I handle the binary relationships that exist between the object of concern and other objects in the domain?

This can be done with a comparison table. 

I have applied fuzzy soft sets for decision making in an imprecise environment and

have found it to be an effective technique.

Following paper elaborates on this approach:

http://www.sciencedirect.com/science/article/pii/S0377042706002160

Your Queries:

Q) Can fuzzy soft set be used without the comparison table?

A comparison table used in Fuzzy soft sets is required for element/parameter wise comparison of objects. Here by parameter, I mean the attributes which describe the

objects under comparison. The row-sum and column sum of objects is further used for ranking of the objects compared.  In most  of the decision making problems, after construction of comparison table the next step is computation of score followed by decision. So a comparison table is very much essential in decision making problems.  

Q) But what happens when am only concern about the truthfulness of a particular object in the domain, must I also have to make comparison with other objects in that domain?

By Truthfulness of a particular object in the domain do you mean you are only concerned with full/partial membership in the fuzzy sets? This can be achieved 

with regular fuzzy sets as well.

Q) Also how best can I handle the binary relationships that exist between the object of concern and other objects in the domain?

This can be done with a comparison table.