This paper presents a partial matching strategy for phrase-based statistical machine translation (PBSMT). Source phrases which do not appear in the training corpus can be translated by word substitution according to p...
详细信息
Dynamic description logic (DDL) is among the few emerging service composition solutions through logical reasoning. To overcome low efficiency and lacking context-aware support of DDL reasoning, we propose a new DDL-ba...
详细信息
Video copy detection is essentially a problem of large scale pattern matching. Various copy attacks which change the visual appearance impose hazard on this task. Based on the spatio-temporal consistency, our algorith...
详细信息
This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual information around rules and information o...
详细信息
This paper proposes a novel lexicalized approach for rule selection for syntax-based statistical machine translation (SMT). We build maximum entropy (MaxEnt) models which combine rich context information for selecting...
详细信息
Firstly, a new Clustering algorithm based on Hyper Surface (CHS) is put forward in this paper. CHS needs no domain knowledge to determine input parameters. However, it is difficult to process locally dense data for CH...
详细信息
This paper presents a partial matching strategy for phrase-based statistical machine translation (PBSMT). Source phrases which do not appear in the training corpus can be translated by word substitution according to p...
详细信息
In order to reduce the complexity of hologram generation and holographic display, for the first time the paper combines Gerchberg-Saxton iterative algorithm with Lohmann coding to make phase-only hologram and designs ...
详细信息
Analytical study or designing of large‐scale nonlinear neural circuits, especially for chaotic neural circuits, is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framewo...
Analytical study or designing of large‐scale nonlinear neural circuits, especially for chaotic neural circuits, is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells’ dynamical equations. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system, and we proved that if a neural system works in a non‐chaotic way, a suitable fuzzy logical framework can be found and we can analyze or design such kind neural system similar to analyze or design a digit computer, but if a neural system works in a chaotic way, an approximation is needed for understanding the function of such neural system.
In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. We first segregate interactive feedback into 3 distinct types (recall-driven relevance feedback, precision-driven active...
详细信息
ISBN:
(纸本)9781605580708
In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. We first segregate interactive feedback into 3 distinct types (recall-driven relevance feedback, precision-driven active learning and locality-driven relevance feedback) so that a generic interaction mechanism with more flexibility can be performed to cover different search queries and different video corpuses. Our system facilitates expert searchers to flexibly decide on the types of feedback they want to employ under different situations. To cater to the large number of novice users (non-expert users), an adaptive option is built-in to learn the expert user behavior so as to provide recommendations on the next feedback strategy, leading to a more precise and personalized search for the novice users. Experimental results on TRECVID news video corpus demonstrate that our proposed adaptive multiple feedback strategies are effective. Copyright 2008 ACM.
暂无评论