New York University (NYU) participated in three tracks of the 2014 TAC-KBP evaluation: English Slot Filling, Cold Start and Entity Discovery and Linking. While this year is the first time and second time we participated in entity discovery and linking (EDL) and cold start respectively, we have been working on the slot filling task for several years. With additional development time this year, o...

The recommender system is one of indispensable components in many e-commerce websites. One of the major challenges that largely remains open is the cold-start problem, which can be viewed as a barrier that keeps the cold-start users/items away from the existing ones. In this paper, we aim to break through this barrier for cold-start users/items by the assistance of existing ones. In particular,...

In this investigation, a parametric study was performed using the transient cold-start model presented in our previous paper, in which the ice melting process and additional constitutive relations were newly included for transient cold-start simulations of polymer electrolyte fuel cells (PEFCs) from a sub-zero temperature (-20°C) to a normal operating temperature (80°C). The focus is placed on ...

Using only implicit data, many recommender systems fail in general to provide a precise set of recommendations to users with limited interaction history. This issue is regarded as the “Cold Start” problem and is typically resolved by switching to content-based approaches where extra costly information is required. In this paper, we use a dimensionality reduction algorithm, Word2Vec (W2V), origi...

The explosive growth of the World Wide Web leads to the fast advancing development of e-commerce techniques. Recommender systems, which use personalised information filtering techniques to generate a set of items suitable to a given user, have received considerable attention. Userand item-based algorithms are two popular techniques for the design of recommender systems. These two algorithms are...

Generating personalized movie recommendations to users is a problem that most commonly relies on user-movie ratings. These ratings are generally used either to understand the user preferences or to recommend movies that users with similar rating patterns have rated highly. However, movie recommenders are often subject to the ColdStart problem: new movies have not been rated by anyone, so, they ...

IJCAI-16 Contest Brick-and-Mortar Store Recommendation with Budget Constraints is about buyer nearby brick-and-mortar stores recommendation. The main task of this competition focuses on predicting nearby store buying action when users enter new areas they rarely visited in the past. The contest has two novelties: first, given huge amount of online user behavior with on-site shopping record of m...

The temporary ineffectiveness of motor vehicle emission controls at startup causes emission rates to be much higher for a short period after starting than during fully warmed, or stabilized, vehicle operation. Official motor vehicle emission inventories estimate that excess emissions during cold-start operation contribute a significant fraction of all hydrocarbon, carbon monoxide (CO), and nitr...