Web Technologies - Science topic

Of course, mobile applications have made great progress with the arrival of smartphones and Android, and will continue to .

Polite web robots introduce themselves in the User Agent field.

You can search for substrings like 'bot', 'spider',

'crawler', 'slurp'.

Rarely a robot tries to access a search page.

The robots tests whether a webpage has a search engine

and makes a GET request for something like

/search?...

Regards,

Joachim

A useful compromise between more structured and less structured interviews is what is known as a funnel approach. The analogy is that the interview starts more broadly (with less structured questions) and then narrows down (into more structured questions). This allows you to hear the participant's perspective first, before you introduce the topics that interest you.

I think that crowfunfing campaigns may help entrepreneurs to obtain feedback on their market demand and may complement the financing needs of the young firm. But the idea underpinning the  firm's project may be replicated quickly by others, if revealed on a platform. Moreover, the presence on platforms of professional investors (venture capitalists) reduces the entrepreneur's incentives to undertake a crowfunding campaign.. Perhaps the optimal funding structure turns out to be a mix of crowfunding and professionnal investors financing schemes.

An ontology, e.g. encoded in OWL, can be perceived as a graph, whose nodes are classes, restrictions, individuals and literals, whereas edges are attributed with object or datatype properties or are taxonomic relations.

Obviously, any graph can be generated with graph grammar rules, e.g. single pushouts, double pushouts, see http://en.wikipedia.org/wiki/Graph_rewriting.

However, such mechanical generation would never result in a domain ontology. It would be just a random graph with random names of classes and properties.

If you take as input a domain ontology constituting a TBox, i.e. classes, restrictions and properties, you may generate a model (ABox) consistent with it being. a set of individuals and literals linked by relations. This can be done in quite a strightforward way.

Generating TBox is much harder, you should pull in actual knowledge into the ontology, e,g, from text documents. It is no longer a generation task, rather a relationship mining. As stated Saravana Balaji B, this requires employing NLP techniques: looking for concept candidates (nouns followed by adjectives) and relation candidates (verbs).

Dwell time must not be too short (info irrelevant) or too long (not understandable).

If people are going directly to the page required, and not going via the home page, this is a good sign.

A Google of: sher-e-kashmir university application form

takes me right to a home page http://www.skuastkashmir.ac.in/

The page is full of hard to read highlighted links, garish colour, NEW bling, and distracting panes scrolling vertically and horizontally. Does that give the right impression that this is a serious institution?

Compare for example with http://www.unisa.ac.za/Default.asp?Cmd=ViewContent&ContentID=15670