Proekt tipovogo samannogo doma pod cherepichnoĭ krysheĭ dli︠a︡ evreĭskikh pereselent︠s︡ev obsluzhivaemykh Agro-Dzhoĭntom

Digital image

Ogorody kolkhoza imeni Molotova v poselke "Gortenshtadt"

Digital image

Karta Kryma s naneseniem evreǐskikh pereselencheskikh otvodov

Digital image

Proekt tipovogo zdanii︠a︡ dli︠a︡ pereselencheskikh uchastkov, obsluzhivaemykh Agrodzhoĭntom

Digital image

Proekt tipovoĭ kooperativnoĭ lavki dli︠a︡ evreĭskikh pereselencheskikh poselkov, obsluzhivaemykh Agrodzhoĭntom

Digital image

Proekt syrovarni dli︠a︡ pereselencheskikh uchastkov obsluzhivaemykh Agro-dzhoĭntom

Digital image

Proekt zdanii︠a︡ mashinogo sarai︠a︡

Digital image

Tipovoĭ proekt inkubatorii︠a︡

Digital image

Proekt tipovoĭ shkoly dli︠a︡ pereselencheskikh uchastkov obsluzhivaemykh Agrodzhoĭntom

Digital image

Letter of thanks to Joseph Rosen

Digital image

Letter of thanks to Joseph Rosen from the Ekaterinoslav community

Digital image

Letter of thanks to Joseph Rosen from the Ukrainian Jewish community, Kharkiv

Digital image

Zapys zemelʹnyĭ Na pravo korystovanni︠a︡ zemli︠u︡, shcho znakhoditʹsi︠a︡ v Odeskoï guberni Peryletravenʹsʹkyĭ okruzi Kantakuzenʹsʹy raʹoni pid nazvoi︠u︡ Trudovyshyĭ artilʹ Slava

Digital image

Zapys zemelʹnyĭ Na pravo korystovanni︠a︡ zemli︠u︡, shcho znakhoditʹsi︠a︡ v Odeskoï guberni Peryletravenʹsʹkyĭ okruzi Kantakuzenʹsʹy raʹoni pid nazvoi︠u︡ Trudovyshyĭ artilʹ Slava

Digital image

Mining topical relevant patterns for multi-document summarization

Multi-document summarization addressing the problem of information overload has been widely utilized in the various real-world applications. Most of existing approaches adopt term-based representation for documents which limit the performance of multi-document summarization systems. In this paper, we proposed a novel pattern-based topic model (PBTMSum) for the task of the multi-document summarization. PBTMSum combining pattern mining techniques with LDA topic modelling could generate discriminative and semantic rich representations for topics and documents so that the most representative and non-redundant sentences can be selected to form a succinct and informative summary. Extensive experiments are conducted on the data of document understanding conference (DUC) 2007. The results prove the effectiveness and efficiency of our proposed approach.