10 cách khắc phục sự cố DNS Resolution- phần 2
3. Ping địa chỉ IP của host mà bạn muốn truy cập đến (nếu biết) Một cách nhanh để chứng tỏ nguyên nhân là vấn đề của DNS chứ không phải vấn đề của mạng là ping đến địa chỉ IP của host mà bạn đang muốn truy cập đến. Nếu kết nối đến tên miền thất bại nhưng kết nối đến địa chỉ IP thành công thì bạn sẽ biết rằng vấn đề của mình nằm ở DNS. Tuy nhiên nếu DNS Server của bạn không hoạt động thì rất...
10 cách khắc phục sự cố DNS Resolution
Trong bài này chúng tôi sẽ giới thiệu cho các bạn 10 cách để khắc phục sự cố các vấn đề phát sinh với DNS Resolution. Giới thiệu Tất cả chúng ta đều cần đến một DNS Resolution đích thực cho các ứng dụng mạng của mình.
Module 3: Resolving Names
Multimedia: Introduction to the Name Resolution Process Viewing Names on a Client Configuring Host Name Resolution Configuring NetBIOS Name Resolution
Multimedia: Introduction to the Name Resolution Process
The objective of this presentation is to provide a high-level overview of the name resolution process in the network infrastructure After this presentation, you will be able to: Explain what a host name is Explain what a NetBIOS name is Describe how the name resolution process works
Lesson: Viewing Names on a Client
How Names Are Mapped to IP Addres...
IP best-effort packet-delivery service:
IP addressing and packet forwarding with datagram mode.
Multiplexing accomplished by transport protocols (TCP, UDP).
And how to build on top of the narrow waist:
Domain Name System (DNS) for resolution between name and
Dynamic host configuration protocol-DHCP for IP
This paper presents a supervised pronoun anaphora resolution system based on factorial hidden Markov models (FHMMs). The basic idea is that the hidden states of FHMMs are an explicit short-term memory with an antecedent buffer containing recently described referents. Thus an observed pronoun can ﬁnd its antecedent from the hidden buffer, or in terms of a generative model, the entries in the hidden buffer generate the corresponding pronouns.
In this paper, we view coreference resolution as a problem of ranking candidate partitions generated by different coreference systems. We propose a set of partition-based features to learn a ranking model for distinguishing good and bad partitions. Our approach compares favorably to two state-of-the-art coreference systems when evaluated on three standard coreference data sets.
Traditionally astrophysics has concerned itself with minimum time-scales measured
in hours rather than seconds. This was understandable as the available recording
media were slow; e.g. chart recorders and photographic plates. In the 1950s, 60s
and 70s wavebands away from the optical were developed; from ground based
radio studies to space and balloon borne high energy work. In contrast to optical
wavelengths instrumentation in these (high and low energy) regimes was capable
of time resolutions of less than a second....
Current work on automatic opinion mining has ignored opinion targets expressed by anaphorical pronouns, thereby missing a signiﬁcant number of opinion targets. In this paper we empirically evaluate whether using an off-the-shelf anaphora resolution algorithm can improve the performance of a baseline opinion mining system. We present an analysis based on two different anaphora resolution systems.
While world knowledge has been shown to improve learning-based coreference resolvers, the improvements were typically obtained by incorporating world knowledge into a fairly weak baseline resolver. Hence, it is not clear whether these beneﬁts can carry over to a stronger baseline. Moreover, since there has been no attempt to apply different sources of world knowledge in combination to coreference resolution, it is not clear whether they offer complementary beneﬁts to a resolver.
This paper describes a proposal for Portuguese possessive pronominal anaphor (PPA) resolution, a problem little considered so far. Particularly, we address the problem of Portuguese 3rd person intrasentential PPAs seu/sua/seus/suas (his/her/their/its, for human and non-human subjects in English), which constitute 30% of pronominal occurrences in our corpus (Brazilian laws about environment protection).
A method for resolving the ellipses that appear in Japanese dialogues is proposed. This method resolves not only the subject ellipsis, but also those in object and other grammatical cases. In this approach, a machine-learning algorithm is used to select the attributes necessary for a resolution. A decision tree is built, and used as the actual ellipsis resolver. The results of blind tests have shown that the proposed method was able to provide a resolution accuracy of 91.7% for indirect objects, and 78.7% for subjects with a verb predicate. ...
This paper presents a new model of anaphoric processing that utilizes the establishment of coherence relations between clauses in a discourse. We survey data that comprises a currently stalemated argument over whether VP-ellipsis is an inherently syntactic or inherently semantic phenomenon, and show that the data can be handled within a uniform discourse processing architecture. This architecture, which revises the dichotomy between ellipsis vs.
Despite the existence of several noun phrase coreference resolution data sets as well as several formal evaluations on the task, it remains frustratingly difﬁcult to compare results across different coreference resolution systems. This is due to the high cost of implementing a complete end-to-end coreference resolution system, which often forces researchers to substitute available gold-standard information in lieu of implementing a module that would compute that information.
In this paper, we present an unsupervised framework that bootstraps a complete coreference resolution (CoRe) system from word associations mined from a large unlabeled corpus. We show that word associations are useful for CoRe – e.g., the strong association between Obama and President is an indicator of likely coreference. Association information has so far not been used in CoRe because it is sparse and difﬁcult to learn from small labeled corpora.
We present an ILP-based model of zero anaphora detection and resolution that builds on the joint determination of anaphoricity and coreference model proposed by Denis and Baldridge (2007), but revises it and extends it into a three-way ILP problem also incorporating subject detection. We show that this new model outperforms several baselines and competing models, as well as a direct translation of the Denis / Baldridge model, for both Italian and Japanese zero anaphora.
This paper explores how to apply the notion of caching introduced by Walker (1996) to the task of zero-anaphora resolution. We propose a machine learning-based implementation of a cache model to reduce the computational cost of identifying an antecedent. Our empirical evaluation with Japanese newspaper articles shows that the number of candidate antecedents for each zero-pronoun can be dramatically reduced while preserving the accuracy of resolving it.
We aim to shed light on the state-of-the-art in NP coreference resolution by teasing apart the differences in the MUC and ACE task deﬁnitions, the assumptions made in evaluation methodologies, and inherent differences in text corpora. First, we examine three subproblems that play a role in coreference resolution: named entity recognition, anaphoricity determination, and coreference element detection.
Syntactic knowledge is important for pronoun resolution. Traditionally, the syntactic information for pronoun resolution is represented in terms of features that have to be selected and deﬁned heuristically. In the paper, we propose a kernel-based method that can automatically mine the syntactic information from the parse trees for pronoun resolution. Speciﬁcally, we utilize the parse trees directly as a structured feature and apply kernel functions to this feature, as well as other normal features, to learn the resolution classiﬁer.
We approach the zero-anaphora resolution problem by decomposing it into intra-sentential and inter-sentential zeroanaphora resolution. For the former problem, syntactic patterns of the appearance of zero-pronouns and their antecedents are useful clues. Taking Japanese as a target language, we empirically demonstrate that incorporating rich syntactic pattern features in a state-of-the-art learning-based anaphora resolution model dramatically improves the accuracy of intra-sentential zero-anaphora, which consequently improves the overall performance of zeroanaphora resolution. ...
In this paper we focus on how to improve pronoun resolution using the statisticsbased semantic compatibility information. We investigate two unexplored issues that inﬂuence the effectiveness of such information: statistics source and learning framework. Speciﬁcally, we for the ﬁrst time propose to utilize the web and the twin-candidate model, in addition to the previous combination of the corpus and the single-candidate model, to compute and apply the semantic information. t