Large networks not only have a large number of vertices but also have a large number of edges. Although such networks are generally sparse they are usually difficult to visualise, even locally. This paper considers the case where large weights on edges represent similarity between the corresponding end-vertices. We follow two main ideas in this paper. The first one is network pruning, that is removal of edges that makes the resulting network more manageable while keeping the main characteristic of the original network. The other idea is to partition the network vertex set in such a way that the induced connected components represent groups of network elements that fit together. Furthermore, we assume that the vertices of the network are labeled by types. Here we apply our approach to co-authorship network of researchers in Slovenia in order to identify research groups, finding group leaders and the degree of interdisciplinarity of the group. For the network pruning phase we use a MST-pathfinder network and for vertex partition appropriate linecuts. Each cluster is assigned a distribution of types. In this case, the types correspond to scientific fields, also known as research interests of authors. A measure of interdisciplinarity of research group is derived from such a distribution. Povzetek: Velika omrežja nimajo le mnogo vozlišč, ampak imajo tudi mnogo povezav.Čeprav so običajno taka omrežja redka, so nepregledna in jih je težko prikazati na sliki, tudi lokalno. Ta prispevek obravnava omrežja, pri katerih velike vrednosti uteži na povezavah pomenijo podobnost pripadajočih krajišč. V prispevku sledimo dvema glavnima idejama. Prva je kleščenje omrežja, to je odstranitev manj pomembnih povezav, zaradičesar je nastalo omrežje bolj obvladljivo, hkrati pa se ohrani glavna značilnost prvotnega omrežja. Druga ideja je razdeliti vozlišča omrežja tako, da inducirane povezane komponente predstavljajo skupine omrežnih elementov, ki se med seboj prilegajo. Poleg tega predpostavljamo, da so vozlišča omrežja označena s tipi. V tem prispevku uporabljamo naš pristop k omrežju soavtorstev raziskovalcev v Sloveniji z namenom identifikacije raziskovalnih skupin, iskanja voditeljev skupin in stopnje interdisciplinarnosti skupine. Za fazo kleščenja omrežja uporabljamo usmerjevalno omrežje (MST-pathfinder network), za vozliščno razbitje pa ustrezne reze povezav. Vsaki skupini je dodeljena porazdelitev tipov. Mero interdisciplinarnosti raziskovalne skupine izpeljemo iz takšne porazdelitve. V tem primeru tipi predstavljajo znanstvena področja, oz. raziskovalne interese avtorjev.
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