Reference Hashed
نویسنده
چکیده
This paper argues for a novel data structure for the representation of discourse referents. A so-called hashing list is employed to store discourse referents according to their grammatical features. The account proposed combines insights from several theories of discourse comprehension. Segmented Discourse Representation Theory (Asher, 1993) is enriched by the ranking system developed in centering theory (Grosz et al., 1995). In addition, a tree logic is used to represent underspecification within the discourse structure (Schilder, 1998).
منابع مشابه
Fast Information-Theoretic Agglomerative Co-clustering
Our algorithm iteratively merges those clusters whose merge yields a lower objective cost. However, operations such as finding nearest neighbors or closest pair of clusters are expensive, especially in high dimensions. To quickly find highly similar clusters to be merged, we exploit the Locality-Sensitive Hashing (LSH) technique, which we briefly describe in this section. Simply put, LSH [2] is...
متن کاملHash , Don ’ t Cache ( the Page Table ) Idan Yaniv
Radix page tables as implemented in the x86-64 architecture incur a penalty of four memory references for address translation upon each TLB miss. These 4 references become 24 in virtualized setups, accounting for 5%–90% of the runtime and thus motivating chip vendors to incorporate page walk caches (PWCs). Counterintuitively, an ISCA 2010 paper found that radix page tables with PWCs are superio...
متن کاملAnalysis of Forest of Hashed Exponential Trees
Exponential Tree in the form of forest is proposed in such a manner that(a) it provides faster access of a node and, (b) it becomes more compatible with the parallel environment. Empirically, it has been show that the proposed method decreases the total internal path length of an Exponential Tree quite considerably. The experiments were conducted by creating three different data structures usin...
متن کاملA Locality Sensitive Hashing Filter for Encrypted Vector Databases
We introduce a filtering methodology based on locality-sensitive hashing (LSH) and whitening transformation to reduce candidate tuples between which encrypted vector databases (EVDBs) must compute similarity for query processing. The LSH hashing methodology is efficient for estimating similarities between two vectors. It hashes a vector space using randomly chosen vectors. We can filter vectors...
متن کاملFast, Accurate Detection of 100,000 Object Classes on a Single Machine: Technical Supplement
In the paper [1] published in CVPR, we presented a method that can directly use deformable part models (DPMs) trained as in [3]. After training, HOG based part filters are hashed, and, during inference, counts of hashing collisions summed over all hash bands serve as a proxy for part-filter / sliding-window dot products, i.e., filter responses. These counts are an approximation and so we take t...
متن کامل