[PDF] Top 20 Joint Inference for Knowledge Base Population
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Joint Inference for Knowledge Base Population
... a joint framework for the task of populating KBs with new knowledge facts, which performs joint inference on two subtasks, maximizes their preliminary scores, fulfills the type expectations of ... See full document
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Probabilistic Inference for Cold Start Knowledge Base Population with Prior World Knowledge
... Building knowledge bases (KB) automat- ically from text corpora is crucial for many applications such as question an- swering and web ...world knowledge at the corpus ...bilistic joint ... See full document
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Estimating Mutation Parameters, Population History and Genealogy Simultaneously From Temporally Spaced Sequence Data
... constant-size population model with the HKY mutation found a suite of MCMC updates that do the ...and population model and a GTR mutation ...the joint estimation of mutation as the true ...and ... See full document
14
Challenges in the Knowledge Base Population Slot Filling Task
... Inference: as we will show later, KBP requires systems to perform quite sophisticated ...predefined inference rules between slots (relations and ...long-distance inference cases can be handled by ... See full document
6
Distantly Supervised Web Relation Extraction for Knowledge Base Population
... self is an unsupervised domain-independent approach, but might not necessarily be useful for scenarios for which only a small corpus of documents or only a very small number of relation tuples is available in the ... See full document
15
Random Walk Inference and Learning in A Large Scale Knowledge Base
... The Path Ranking Algorithm (PRA) we use is similar to that described elsewhere (Lao and Cohen, 2010b), except that to achieve efficient model learning, the paths between a and b are determined by the statistics from a ... See full document
11
Joint Inference for Knowledge Extraction from Biomedical Literature
... leverage joint inference among events and arguments for mutual ...Some joint approaches have been proposed, but they still lag much behind in ...first joint approach for bio- event extraction ... See full document
9
Stacked Ensembles of Information Extractors for Knowledge Base Population
... For the past few years, NIST has been conducting the English Slot Filling (ESF) Task in the Knowl- edge Base Population (KBP) track among various other tasks as a part of the Text Analysis Con- ... See full document
11
Importance sampling for unbiased on demand evaluation of knowledge base population
... Separately, we evaluate the efficacy of the adaptive sample selection method described in Section 4.3 through another simulated experiment. In each trial of this experiment, we evaluate the top 40 systems in random ... See full document
11
Knowledge Base Population: Successful Approaches and Challenges
... Slot Filling can also benefit from extracting re- vertible queries from the context of any target query, and conducting global ranking or reasoning to refine the results. CUNY and IBM developed recursive reasoning ... See full document
11
Knowledge Extraction and Joint Inference Using Tractable Markov Logic
... Non-recursive probabilistic context-free grammars (PCFGs) (Chi, 1999) can be compactly encoded in TML. Non-terminals have class-subclass relation- ships to their set of productions. Each production is split into subparts ... See full document
5
Joint Inference for Fine grained Opinion Extraction
... a joint inference model that leverages knowledge from predictors that optimize subtasks of opinion extraction, and seeks a glob- ally optimal ...our joint inference approach ... See full document
10
Pocket Knowledge Base Population
... each entity, we perform a joint search for it and the query. These entity co-occurrences will form the spokes in the PKB and be used to characterize the relationship between and relatedness to the query. ... See full document
6
Combining Supervised and Unsupervised Enembles for Knowledge Base Population
... Ensembling multiple systems is a well known stan- dard approach to improving accuracy in several ma- chine learning applications (Dietterich, 2000). En- sembles have been applied to parsing (Henderson and Brill, 1999), ... See full document
6
Type Sensitive Knowledge Base Inference Without Explicit Type Supervision
... the base model to unit norm performs better than using L2 ...corresponding base model on all measures, under- scoring the value of type compatibility ...our knowledge, the results of our typed models ... See full document
6
KnowledgeNet: A Benchmark Dataset for Knowledge Base Population
... a knowledge base (Wikidata) with facts expressed in natural language text on the ...of knowledge base population systems as a whole, unlike previous benchmarks that are more suitable ... See full document
10
Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference
... We use Coq, an interactive proof assistant based on the Calculus of Inductive Constructions (CiC), in order to im- plement an RTE system with our method of axiom inser- tion. Although Coq is known as an interactive proof ... See full document
8
Improving Learning and Inference in a Large Knowledge Base using Latent Syntactic Cues
... In Figure 1, the KB graph (only solid edges) is dis- connected, thereby making it impossible for PRA to discover any relationship between Alex Rodriguez and World Series. However, addition of the two edges with SVO-based ... See full document
6
Securing Valued Data by using Encryption Algorithms with the help of Inference Engine and Knowledge Base
... This paper focuses on selecting the appropriate algorithm depending on the value of the data or information. This paper helps to secure the data based on the value, as if the data value is high, it needs to be more ... See full document
5
Design and Implementing an Efficient Expert Assistance System for Car Evaluation via Fuzzy Logic Controller
... The parallelism of the knowledge base and inference engine improves system performance [7]. The advantage behind this procedure is to overcome the repetition of incorrect decisions during the ... See full document
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