Relation classification is a crucial ingredient in numerous information extraction systems seeking to mine structured facts from text.We propose novel convolutional neural network architecture for this task, relying on two levels of attention order better discern patterns heterogeneous contexts.This enables endto-end learning task-specific labeled data, forgoing the need external knowledge such as explicit dependency structures.Experiments show that our model outperforms previous...

Linlin Wang, Kang Liu, Zhu Cao, Jun Zhao, Gerard de Melo. Proceedings of the 53rd Annual Meeting Association for Computational Linguistics and 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015.

Morphological segmentation, which aims to break words into meaning-bearing morphemes, is an important task in natural language processing. Most previous work relies heavily on linguistic preprocessing. In this paper, we instead propose novel neural network architectures that learn the structure of input sequences directly from raw and are subsequently able predict morphological boundaries. Our rely Long Short Term Memory (LSTM) units accomplish this, but exploit windows characters capture...

Critics decry cryptocurrency mining as a huge waste of energy, while proponents insist on claiming that it is green industry. Is Bitcoin really worth the energy consumes? The high power consumption has become latest global flashpoint. In this paper, we define Mining Domestic Production (MDP) method to account for final outcome industry's production activities in certain period time, calculate carbon emission per unit output value industry China, and compare with three other traditional...

The emergence of fine-tuning-as-a-service has revealed a new vulnerability in large language models (LLMs). A mere handful malicious data uploaded by users can subtly manipulate the fine-tuning process, leading to compromised alignment state. Existing methods counteract attacks typically require substantial computational resources. Even with parameter-efficient techniques like LoRA, gradient updates remain essential. To address these challenges, we propose Neuron-Level Safety Realignment...

Link prediction is of fundamental importance in network science and machine learning. Early methods consider only simple topological features, while subsequent supervised approaches typically rely on human-labeled data feature engineering. In this work, we present a new representation learning-based approach called SEMAC that jointly exploits fine-grained node features as well the overall graph topology. contrast to SGNS or SVD espoused previous representation-based studies, our model...

Lyric-based song sentiment classification seeks to assign songs appropriate labels such as light-hearted and heavy-hearted. Four problems render vector space model (VSM)-based text approach ineffective: 1) Many words within lyrics actually contribute little sentiment; 2) Nouns verbs used express are ambiguous; 3) Negations modifiers around the keywords make particular contributions 4) Song lyric is usually very short. To address these problems, (s-VSM) proposed represent document. The...

Abstractive summarization is a standard task for written documents, such as news articles.Applying schemes to spoken documents more challenging, especially in situations involving human interactions, meetings.Here, utterances tend not form complete sentences and sometimes contain little information.Moreover, speech disfluencies will be present well recognition errors automated systems.For current attention-based sequence-to-sequence systems, these additional challenges can yield poor...

Wireless sensor network is composed of hundreds nodes involving in limited energy, efficient and low-energy consuming routing algorithm the crucial problem to design. In this paper, LEACH protocol, which a typical clustering has been researched improved based on new different from method determining number clusters heads criterion that chooses cluster-heads. Simulation results indicate advantages reducing energy prolonging lifetime network.

With the growing importance of strategic alliances and supply chains as competitive units, academics practitioners are interested in understanding techniques used by firms to leverage interfirm relationships gain a advantage. Studies conducted Western context underline role relational governance (i.e., modern way), whereas works Chinese highlight guanxi traditional way). Today’s economy operates hybrid business model patterns with coexistence guanxi. Therefore, this study addresses two...

Chinese Spelling Correction (CSC) is the task of detecting and correcting misspelled charac- ters in texts. As an important step for various downstream tasks, CSC confronts two challenges: 1) Character-level errors consist not only spelling but also missing redundant ones that cause variable length between input output texts, which most methods could handle well because consistence texts required by their inherent detection-correction framework. Con- sequently, are considered out- side scope...

Song sentiment analysis attracts much attention in research areas such as acoustic signal processing (ASP) and natural language (NLP). The text-based efforts the NLP community are found to be interesting. As a popular solution, lyric-based classification approach adopts vector space model (VSM) represent lyric text assigns songs labels light-hearted heavy-hearted. Four problems render term-based VSM ineffective. Firstly, many words within song lyrics contribute little expressing sentiment,...

Nowadays, intrusion detection is a technology to effectively avoid number of risks network intrusion. The K-means algorithm widely used in detection. But, the has some shortcomings, such as random selection k value, sensitive initial cluster centers, and low accuracy clustering high-dimensional data. In order make up for these shortcomings algorithm, this paper proposes an AE-Kmeans architecture which combines autoencoder with improved algorithm. realizes dimension reduction feature...

This paper presents the development of 2014 Cambridge University conversational telephone Mandarin Chinese LVCSR system for DARPA BOLT speech translation evaluation. A range advanced modelling techniques were employed to both improve recognition performance and provide a suitable integration with system. These include an improved combination technique using frame level acoustic model via joint decoding. Sequence trained deep neural network (DNN) based hybrid tandem systems combined...

Empathetic response generation requires perceiving and understanding the user's emotion to deliver suitable responses. However, existing models generally lack an ability respond in a persona-specific way, which has been shown play vital role expressing appropriate empathy. To address this problem, we propose novel Transformer-based architecture that incorporates retrieval-augmented prompt learning generate persona-aware empathetic Since personalized emotional resonance is subtle...

As a new method of WebGIS developing, the RIA technology has good development foreground. According to characteristic Flex and RIA, we analyzed architecture based on Flex. In order improve efficiency system, introduced tile double cache technology, vector raster integrated map service. At last, solution was presented certain company system developed. The results demonstrate that developing by is an ideal method.

In this paper, we prove the existence of a nontrivial (weak) solution Brézis–Nirenberg equation for $ (m, p) Laplacian in whole space \mathbb R^N $. Critical problems have been intensively studied last decades, starting with pioneering paper by Brézis and Nirenberg Dirichlet bounded domains Even if obtain solutions via standard variational techniques, step proof is pretty involved requires new ideas delicate use Talenti functions.